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Sample records for ant colony algorithm

  1. Loading pattern optimization using ant colony algorithm

    International Nuclear Information System (INIS)

    Hoareau, Fabrice

    2008-01-01

    Electricite de France (EDF) operates 58 nuclear power plants (NPP), of the Pressurized Water Reactor type. The loading pattern optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R and D has developed automatic optimization tools that assist the experts. LOOP is an industrial tool, developed by EDF R and D and based on a simulated annealing algorithm. In order to improve the results of such automatic tools, new optimization methods have to be tested. Ant Colony Optimization (ACO) algorithms are recent methods that have given very good results on combinatorial optimization problems. In order to evaluate the performance of such methods on loading pattern optimization, direct comparisons between LOOP and a mock-up based on the Max-Min Ant System algorithm (a particular variant of ACO algorithms) were made on realistic test-cases. It is shown that the results obtained by the ACO mock-up are very similar to those of LOOP. Future research will consist in improving these encouraging results by using parallelization and by hybridizing the ACO algorithm with local search procedures. (author)

  2. Improved Ant Colony Clustering Algorithm and Its Performance Study

    Science.gov (United States)

    Gao, Wei

    2016-01-01

    Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

  3. Improved Ant Colony Clustering Algorithm and Its Performance Study

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2016-01-01

    Full Text Available Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering.

  4. An Improved Ant Colony Routing Algorithm for WSNs

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    Tan Zhi

    2015-01-01

    Full Text Available Ant colony algorithm is a classical routing algorithm. And it are used in a variety of application because it is economic and self-organized. However, the routing algorithm will expend huge amounts of energy at the beginning. In the paper, based on the idea of Dijkstra algorithm, the improved ant colony algorithm was proposed to balance the energy consumption of networks. Through simulation and comparison with basic ant colony algorithms, it is obvious that improved algorithm can effectively balance energy consumption and extend the lifetime of WSNs.

  5. Warehouse stocking optimization based on dynamic ant colony genetic algorithm

    Science.gov (United States)

    Xiao, Xiaoxu

    2018-04-01

    In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

  6. Ant colony search algorithm for optimal reactive power optimization

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    Lenin K.

    2006-01-01

    Full Text Available The paper presents an (ACSA Ant colony search Algorithm for Optimal Reactive Power Optimization and voltage control of power systems. ACSA is a new co-operative agents’ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called "Ants" co-operates to find good solution for Reactive Power Optimization problem. The ACSA is applied for optimal reactive power optimization is evaluated on standard IEEE, 30, 57, 191 (practical test bus system. The proposed approach is tested and compared to genetic algorithm (GA, Adaptive Genetic Algorithm (AGA.

  7. Core Business Selection Based on Ant Colony Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Yu Lan

    2014-01-01

    Full Text Available Core business is the most important business to the enterprise in diversified business. In this paper, we first introduce the definition and characteristics of the core business and then descript the ant colony clustering algorithm. In order to test the effectiveness of the proposed method, Tianjin Port Logistics Development Co., Ltd. is selected as the research object. Based on the current situation of the development of the company, the core business of the company can be acquired by ant colony clustering algorithm. Thus, the results indicate that the proposed method is an effective way to determine the core business for company.

  8. Minimum Cost Multicast Routing Using Ant Colony Optimization Algorithm

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    Xiao-Min Hu

    2013-01-01

    Full Text Available Multicast routing (MR is a technology for delivering network data from some source node(s to a group of destination nodes. The objective of the minimum cost MR (MCMR problem is to find an optimal multicast tree with the minimum cost for MR. This problem is NP complete. In order to tackle the problem, this paper proposes a novel algorithm termed the minimum cost multicast routing ant colony optimization (MCMRACO. Based on the ant colony optimization (ACO framework, the artificial ants in the proposed algorithm use a probabilistic greedy realization of Prim’s algorithm to construct multicast trees. Moving in a cost complete graph (CCG of the network topology, the ants build solutions according to the heuristic and pheromone information. The heuristic information represents problem-specific knowledge for the ants to construct solutions. The pheromone update mechanisms coordinate the ants’ activities by modulating the pheromones. The algorithm can quickly respond to the changes of multicast nodes in a dynamic MR environment. The performance of the proposed algorithm has been compared with published results available in the literature. Results show that the proposed algorithm performs well in both static and dynamic MCMR problems.

  9. Efficient distribution of toy products using ant colony optimization algorithm

    Science.gov (United States)

    Hidayat, S.; Nurpraja, C. A.

    2017-12-01

    CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.

  10. Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

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    Yunpeng Wang

    2014-01-01

    Full Text Available We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

  11. Automatic fault extraction using a modified ant-colony algorithm

    International Nuclear Information System (INIS)

    Zhao, Junsheng; Sun, Sam Zandong

    2013-01-01

    The basis of automatic fault extraction is seismic attributes, such as the coherence cube which is always used to identify a fault by the minimum value. The biggest challenge in automatic fault extraction is noise, including that of seismic data. However, a fault has a better spatial continuity in certain direction, which makes it quite different from noise. Considering this characteristic, a modified ant-colony algorithm is introduced into automatic fault identification and tracking, where the gradient direction and direction consistency are used as constraints. Numerical model test results show that this method is feasible and effective in automatic fault extraction and noise suppression. The application of field data further illustrates its validity and superiority. (paper)

  12. Software Piracy Detection Model Using Ant Colony Optimization Algorithm

    Science.gov (United States)

    Astiqah Omar, Nor; Zakuan, Zeti Zuryani Mohd; Saian, Rizauddin

    2017-06-01

    Internet enables information to be accessible anytime and anywhere. This scenario creates an environment whereby information can be easily copied. Easy access to the internet is one of the factors which contribute towards piracy in Malaysia as well as the rest of the world. According to a survey conducted by Compliance Gap BSA Global Software Survey in 2013 on software piracy, found out that 43 percent of the software installed on PCs around the world was not properly licensed, the commercial value of the unlicensed installations worldwide was reported to be 62.7 billion. Piracy can happen anywhere including universities. Malaysia as well as other countries in the world is faced with issues of piracy committed by the students in universities. Piracy in universities concern about acts of stealing intellectual property. It can be in the form of software piracy, music piracy, movies piracy and piracy of intellectual materials such as books, articles and journals. This scenario affected the owner of intellectual property as their property is in jeopardy. This study has developed a classification model for detecting software piracy. The model was developed using a swarm intelligence algorithm called the Ant Colony Optimization algorithm. The data for training was collected by a study conducted in Universiti Teknologi MARA (Perlis). Experimental results show that the model detection accuracy rate is better as compared to J48 algorithm.

  13. Multiconstrained Network Intensive Vehicle Routing Adaptive Ant Colony Algorithm in the Context of Neural Network Analysis

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    Shaopei Chen

    2017-01-01

    Full Text Available Neural network models have recently made significant achievements in solving vehicle scheduling problems. Adaptive ant colony algorithm provides a new idea for neural networks to solve complex system problems of multiconstrained network intensive vehicle routing models. The pheromone in the path is changed by adjusting the volatile factors in the operation process adaptively. It effectively overcomes the tendency of the traditional ant colony algorithm to fall easily into the local optimal solution and slow convergence speed to search for the global optimal solution. The multiconstrained network intensive vehicle routing algorithm based on adaptive ant colony algorithm in this paper refers to the interaction between groups. Adaptive transfer and pheromone update strategies are introduced based on the traditional ant colony algorithm to optimize the selection, update, and coordination mechanisms of the algorithm further. Thus, the search task of the objective function for a feasible solution is completed by the search ants. Through the division and collaboration of different kinds of ants, pheromone adaptive strategy is combined with polymorphic ant colony algorithm. It can effectively overcome some disadvantages, such as premature stagnation, and has a theoretical significance to the study of large-scale multiconstrained vehicle routing problems in complex traffic network systems.

  14. Application of ant colony Algorithm and particle swarm optimization in architectural design

    Science.gov (United States)

    Song, Ziyi; Wu, Yunfa; Song, Jianhua

    2018-02-01

    By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.

  15. Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

    Science.gov (United States)

    Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

    2018-03-01

    Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

  16. Single Allocation Hub-and-spoke Networks Design Based on Ant Colony Optimization Algorithm

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    Yang Pingle

    2014-10-01

    Full Text Available Capacitated single allocation hub-and-spoke networks can be abstracted as a mixed integer linear programming model equation with three variables. Introducing an improved ant colony algorithm, which has six local search operators. Meanwhile, introducing the "Solution Pair" concept to decompose and optimize the composition of the problem, the problem can become more specific and effectively meet the premise and advantages of using ant colony algorithm. Finally, location simulation experiment is made according to Australia Post data to demonstrate this algorithm has good efficiency and stability for solving this problem.

  17. Ant Colony Algorithm and Simulation for Robust Airport Gate Assignment

    Directory of Open Access Journals (Sweden)

    Hui Zhao

    2014-01-01

    Full Text Available Airport gate assignment is core task for airport ground operations. Due to the fact that the departure and arrival time of flights may be influenced by many random factors, the airport gate assignment scheme may encounter gate conflict and many other problems. This paper aims at finding a robust solution for airport gate assignment problem. A mixed integer model is proposed to formulate the problem, and colony algorithm is designed to solve this model. Simulation result shows that, in consideration of robustness, the ability of antidisturbance for airport gate assignment scheme has much improved.

  18. Optimum Design of Power System Stabilizer based on Improved Ant Colony Optimization Algorithm

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    Ruba AL-MulaHumadi

    2018-01-01

    Full Text Available This paper presents an improved technique on Ant Colony Optimization (ACO algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB system with power system stabilizer (PSS at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.

  19. Three-dimensional Path Planning for Underwater Vehicles Based on an Improved Ant Colony Optimization Algorithm

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    L.Yang

    2015-12-01

    Full Text Available Three-dimensional path planning for underwater vehicles is an important problem that focuses on optimizing the route with consideration of various constraints in a complex underwater environment. In this paper, an improved ant colony optimization (IACO algorithm based on pheromone exclusion is proposed to solve the underwater vehicle 3D path planning problem. The IACO algorithm can balance the tasks of exploration and development in the ant search path, and enable the ants in the search process to explore initially and develop subsequently. Then, the underwater vehicle can find the safe path by connecting the chosen nodes of the 3D mesh while avoiding the threat area. This new approach can overcome common disadvantages of the basic ant colony algorithm, such as falling into local extremum, poor quality, and low accuracy. Experimental comparative results demonstrate that this proposed IACO method is more effective and feasible in underwater vehicle 3D path planning than the basic ACO model.

  20. Adaptive multimodal continuous ant colony optimization

    OpenAIRE

    Yang, Qiang; Chen, Wei-Neng; Yu, Zhengtao; Gu, Tianlong; Li, Yun; Zhang, Huaxiang; Zhang, Jun

    2017-01-01

    Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization algorithms in preserving high diversity, this paper intends to extend ant colony optimization algorithms to deal with multimodal optimization. First, combined with current niching methods, an adaptive multimodal continuous ant colony optimization algorithm is introduced. In this algorithm, an adaptive parameter a...

  1. Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm

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    Peng Li

    2016-01-01

    Full Text Available The optimal performance of the ant colony algorithm (ACA mainly depends on suitable parameters; therefore, parameter selection for ACA is important. We propose a parameter selection method for ACA based on the bacterial foraging algorithm (BFA, considering the effects of coupling between different parameters. Firstly, parameters for ACA are mapped into a multidimensional space, using a chemotactic operator to ensure that each parameter group approaches the optimal value, speeding up the convergence for each parameter set. Secondly, the operation speed for optimizing the entire parameter set is accelerated using a reproduction operator. Finally, the elimination-dispersal operator is used to strengthen the global optimization of the parameters, which avoids falling into a local optimal solution. In order to validate the effectiveness of this method, the results were compared with those using a genetic algorithm (GA and a particle swarm optimization (PSO, and simulations were conducted using different grid maps for robot path planning. The results indicated that parameter selection for ACA based on BFA was the superior method, able to determine the best parameter combination rapidly, accurately, and effectively.

  2. Comparison Performance of Genetic Algorithm and Ant Colony Optimization in Course Scheduling Optimizing

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    Imam Ahmad Ashari

    2016-11-01

    Full Text Available Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization  algorithm in solving the case of course scheduling.

  3. Ant- and Ant-Colony-Inspired ALife Visual Art.

    Science.gov (United States)

    Greenfield, Gary; Machado, Penousal

    2015-01-01

    Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior.

  4. Optimization of China Crude Oil Transportation Network with Genetic Ant Colony Algorithm

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    Yao Wang

    2015-08-01

    Full Text Available Taking into consideration both shipping and pipeline transport, this paper first analysed the risk factors for different modes of crude oil import transportation. Then, based on the minimum of both transportation cost and overall risk, a multi-objective programming model was established to optimize the transportation network of crude oil import, and the genetic algorithm and ant colony algorithm were employed to solve the problem. The optimized result shows that VLCC (Very Large Crude Carrier is superior in long distance sea transportation, whereas pipeline transport is more secure than sea transport. Finally, this paper provides related safeguard suggestions on crude oil import transportation.

  5. Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

    Science.gov (United States)

    Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

    2018-03-01

    Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

  6. Improving the Power Quality in Tehran Metro Line-Two Using the Ant Colony Algorithm

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    H. Ehteshami

    2017-12-01

    Full Text Available This research aims to survey the improvement of power quality in Tehran metro line 2 using the ant colony algorithm and to investigate all the factors affecting the achievement of this goal. In order to put Tehran on the road of sustainable development, finding a solution for dealing with air pollution is essential. The use of public transportation, especially metro, is one of the ways to achieve this goal. Since the highest share of pollutants in Tehran belongs to cars and mobile sources, relative statistical indicators are estimated through assuming the effect of metro lines development and subsequently reduction of traffic on power quality index.

  7. AUTOMATA PROGRAMS CONSTRUCTION FROM SPECIFICATION WITH AN ANT COLONY OPTIMIZATION ALGORITHM BASED ON MUTATION GRAPH

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    Daniil S. Chivilikhin

    2014-11-01

    Full Text Available The procedure of testing traditionally used in software engineering cannot guarantee program correctness; therefore verification is used at the excess requirements to programs reliability. Verification makes it possible to check certain properties of programs in all possible computational states; however, this process is very complex. In the model checking method a model of the program is built (often, manually and requirements in terms of temporal logic are formulated. Such temporal properties of the model can be checked automatically. The main issue in this framework is the gap between the program and its model. Automata-based programming paradigm gives the possibility to overcome this limitation. In this paradigm, program logic is represented using finite-state machines. The advantage of finite-state machines is that their models can be constructed automatically. The paper deals with the application of mutation-based ant colony optimization algorithm to the problem of finite-state machine construction from their specification, defined by test scenarios and temporal properties. The presented approach has been tested on the elevator doors control problem as well as on randomly generated data. Obtained results show the ant colony algorithm is two-three times faster than the previously used genetic algorithm. The proposed approach can be recommended for inferring control programs for critical systems.

  8. Arc Based Ant Colony Optimization Algorithm for optimal design of gravitational sewer networks

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    R. Moeini

    2017-06-01

    Full Text Available In this paper, constrained and unconstrained versions of a new formulation of Ant Colony Optimization Algorithm (ACOA named Arc Based Ant Colony Optimization Algorithm (ABACOA are augmented with the Tree Growing Algorithm (TGA and used for the optimal layout and pipe size design of gravitational sewer networks. The main advantages offered by the proposed ABACOA formulation are proper definition of heuristic information, a useful component of the ant-based algorithms, and proper trade-off between the two conflicting search attributes of exploration and exploitation. In both the formulations, the TGA is used to incrementally construct feasible tree-like layouts out of the base layout. In the first formulation, unconstrained version of ABACOA is used to determine the nodal cover depths of sewer pipes while in the second formulation, a constrained version of ABACOA is used to determine the nodal cover depths of sewer pipes which satisfy the pipe slopes constraint. Three different methods of cut determination are also proposed to complete the construction of a tree-like network containing all base layout pipes, here. The proposed formulations are used to solve three test examples of different scales and the results are presented and compared with other available results in the literature. Comparison of the results shows that best results are obtained using the third cutting method in both the formulations. In addition, the results indicate the ability of the proposed methods and in particular the constrained version of ABACOA equipped with TGA to solve sewer networks design optimization problem. To be specific, the constrained version of ABACOA has been able to produce results 0.1%, 1% and 2.1% cheaper than those obtained by the unconstrained version of ABACOA for the first, second and the third test examples, respectively.

  9. Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

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    Zhengyu Duan

    2015-11-01

    Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.

  10. An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

    Science.gov (United States)

    Jiang, Ailian; Zheng, Lihong

    2018-03-29

    Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

  11. Simulation study of UAV conflict resolution based on an improved ant colony algorithm

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    Xueli WU

    2018-04-01

    Full Text Available With the gradual opening of the low-altitude airspace and the rapid development of Unmanned Aerial Vehicle(UAV industry, the users of UAV are increasing continuously and the conflicts could occur at any time. It is necessary to develop a reliable UAV conflict resolution algorithm to avoid the danger. This paper proposes an UAV conflict resolution algorithm based on the improved ant colony algorithm with two advantages. Firstly, the algorithm adopts adaptive parameters adjustment strategy, which adjusts the parameters value dynamically according to the quality of the solution, prevents the algorithm premature convergence and improves the accuracy. In addition, the disturbance factors is introduced to the state transition rules of random selected path in order to accelerate the initial convergence. The simulation results have shown that the improved algorithm displays obvious superiority in convergence precision, helping the two UAVs avoiding dangers in time. The algorithm described in this paper could be applied to target identification, path planning and other issues as a general optimized algorithm, which is of great significance and wide application.

  12. Solving optimum operation of single pump unit problem with ant colony optimization (ACO) algorithm

    International Nuclear Information System (INIS)

    Yuan, Y; Liu, C

    2012-01-01

    For pumping stations, the effective scheduling of daily pump operations from solutions to the optimum design operation problem is one of the greatest potential areas for energy cost-savings, there are some difficulties in solving this problem with traditional optimization methods due to the multimodality of the solution region. In this case, an ACO model for optimum operation of pumping unit is proposed and the solution method by ants searching is presented by rationally setting the object function and constrained conditions. A weighted directed graph was constructed and feasible solutions may be found by iteratively searching of artificial ants, and then the optimal solution can be obtained by applying the rule of state transition and the pheromone updating. An example calculation was conducted and the minimum cost was found as 4.9979. The result of ant colony algorithm was compared with the result from dynamic programming or evolutionary solving method in commercial software under the same discrete condition. The result of ACO is better and the computing time is shorter which indicates that ACO algorithm can provide a high application value to the field of optimal operation of pumping stations and related fields.

  13. A multi-objective Pareto ant colony algorithm for the Multi-Depot Vehicle Routing problem with Backhauls

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    Jhon Jairo Santa Chávez

    2016-01-01

    Full Text Available This paper presents a multiobjective ant colony algorithm for the Multi-Depot Vehicle Routing Problem with Backhauls (MDVRPB where three objectives of traveled distance, traveling times and total consumption of energy are minimized. An ant colony algorithm is proposed to solve the MDVRPB. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. The effectiveness of the proposed approach is examined by considering a set of instances adapted from the literature. The computational results show high quality results within short computing times.

  14. DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM

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    H. Chen

    2015-07-01

    Full Text Available In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy.

  15. Proposed algorithm to improve job shop production scheduling using ant colony optimization method

    Science.gov (United States)

    Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

    2017-12-01

    This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

  16. Optimum Layout for Sensors in Water Distribution Networks through Ant Colony Algorithm: A Dual Use Vision

    Directory of Open Access Journals (Sweden)

    Seyed Mehdi Miri

    2014-07-01

    Full Text Available The accidental or intentional entry of contaminants or self-deterioration of the water quality within the network itself can severely harm public health. Efficient water quality monitoring is one of the most important tools to guarantee a reliable potable water supply to consumers of drinking water distribution systems. Considering the high purchase, installation and maintenance cost of sensors in water distribution networks deploying two independent sensor networks within one distribution system is not only bounded by physical constraints but also is not a cost-effective approach. Therefore, need for combining different objectives and designing sensor network to simultaneity satisfying these objectives is felt. Sensors should comply with dual use benefits. Sensor locations and types should be integrated not only for achieving water security goals but also for accomplishing other water utility objectives, such as satisfying regulatory monitoring requirements or collecting information to solve water quality problems. In this study, a dual use vision for the sensor layout problem in the municipal water networks, is formulated and solved with the ant colony algorithm.

  17. Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.

    Science.gov (United States)

    Schroeders, Ulrich; Wilhelm, Oliver; Olaru, Gabriel

    2016-01-01

    The advent of large-scale assessment, but also the more frequent use of longitudinal and multivariate approaches to measurement in psychological, educational, and sociological research, caused an increased demand for psychometrically sound short scales. Shortening scales economizes on valuable administration time, but might result in inadequate measures because reducing an item set could: a) change the internal structure of the measure, b) result in poorer reliability and measurement precision, c) deliver measures that cannot effectively discriminate between persons on the intended ability spectrum, and d) reduce test-criterion relations. Different approaches to abbreviate measures fare differently with respect to the above-mentioned problems. Therefore, we compare the quality and efficiency of three item selection strategies to derive short scales from an existing long version: a Stepwise COnfirmatory Factor Analytical approach (SCOFA) that maximizes factor loadings and two metaheuristics, specifically an Ant Colony Optimization (ACO) with a tailored user-defined optimization function and a Genetic Algorithm (GA) with an unspecific cost-reduction function. SCOFA compiled short versions were highly reliable, but had poor validity. In contrast, both metaheuristics outperformed SCOFA and produced efficient and psychometrically sound short versions (unidimensional, reliable, sensitive, and valid). We discuss under which circumstances ACO and GA produce equivalent results and provide recommendations for conditions in which it is advisable to use a metaheuristic with an unspecific out-of-the-box optimization function.

  18. Monte Carlo simulation using the PENELOPE code with an ant colony algorithm to study MOSFET detectors

    Energy Technology Data Exchange (ETDEWEB)

    Carvajal, M A; Palma, A J [Departamento de Electronica y Tecnologia de Computadores, Universidad de Granada, E-18071 Granada (Spain); Garcia-Pareja, S [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda Carlos Haya, s/n, E-29010 Malaga (Spain); Guirado, D [Servicio de RadiofIsica, Hospital Universitario ' San Cecilio' , Avda Dr Oloriz, 16, E-18012 Granada (Spain); Vilches, M [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda Fuerzas Armadas, 2, E-18014 Granada (Spain); Anguiano, M; Lallena, A M [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)], E-mail: carvajal@ugr.es, E-mail: garciapareja@gmail.com, E-mail: dguirado@ugr.es, E-mail: mvilches@ugr.es, E-mail: mangui@ugr.es, E-mail: ajpalma@ugr.es, E-mail: lallena@ugr.es

    2009-10-21

    In this work we have developed a simulation tool, based on the PENELOPE code, to study the response of MOSFET devices to irradiation with high-energy photons. The energy deposited in the extremely thin silicon dioxide layer has been calculated. To reduce the statistical uncertainties, an ant colony algorithm has been implemented to drive the application of splitting and Russian roulette as variance reduction techniques. In this way, the uncertainty has been reduced by a factor of {approx}5, while the efficiency is increased by a factor of above 20. As an application, we have studied the dependence of the response of the pMOS transistor 3N163, used as a dosimeter, with the incidence angle of the radiation for three common photons sources used in radiotherapy: a {sup 60}Co Theratron-780 and the 6 and 18 MV beams produced by a Mevatron KDS LINAC. Experimental and simulated results have been obtained for gantry angles of 0 deg., 15 deg., 30 deg., 45 deg., 60 deg. and 75 deg. The agreement obtained has permitted validation of the simulation tool. We have studied how to reduce the angular dependence of the MOSFET response by using an additional encapsulation made of brass in the case of the two LINAC qualities considered.

  19. Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

    Directory of Open Access Journals (Sweden)

    Qi Xu

    2012-01-01

    Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

  20. Image Watermarking Algorithm Based on Multiobjective Ant Colony Optimization and Singular Value Decomposition in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Khaled Loukhaoukha

    2013-01-01

    Full Text Available We present a new optimal watermarking scheme based on discrete wavelet transform (DWT and singular value decomposition (SVD using multiobjective ant colony optimization (MOACO. A binary watermark is decomposed using a singular value decomposition. Then, the singular values are embedded in a detailed subband of host image. The trade-off between watermark transparency and robustness is controlled by multiple scaling factors (MSFs instead of a single scaling factor (SSF. Determining the optimal values of the multiple scaling factors (MSFs is a difficult problem. However, a multiobjective ant colony optimization is used to determine these values. Experimental results show much improved performances of the proposed scheme in terms of transparency and robustness compared to other watermarking schemes. Furthermore, it does not suffer from the problem of high probability of false positive detection of the watermarks.

  1. PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm.

    Science.gov (United States)

    Zaidman, Daniel; Wolfson, Haim J

    2016-08-01

    Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ([Formula: see text]) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. danielza@post.tau.ac.il; wolfson@tau.ac.il. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems

    DEFF Research Database (Denmark)

    Lissovoi, Andrei

    the dynamic optimum for finite alphabets up to size μ, while MMAS is able to do so for any finite alphabet size. Parallel Evolutionary Algorithms on Maze. We prove that while a (1 + λ) EA is unable to track the optimum of the dynamic fitness function Maze for offspring population size up to λ = O(n1-ε......This thesis presents new running time analyses of nature-inspired algorithms on various dynamic problems. It aims to identify and analyse the features of algorithms and problem classes which allow efficient optimization to occur in the presence of dynamic behaviour. We consider the following...... settings: λ-MMAS on Dynamic Shortest Path Problems. We investigate how in-creasing the number of ants simulated per iteration may help an ACO algorithm to track optimum in a dynamic problem. It is shown that while a constant number of ants per-vertex is sufficient to track some oscillations, there also...

  3. Application of Ant-Colony-Optimization algorithm for improved management of first flush effects in urban wastewater systems.

    Science.gov (United States)

    Verdaguer, M; Clara, N; Gutiérrez, O; Poch, M

    2014-07-01

    The first flush effect in combined sewer systems during storm events often causes overflows and overloads of the sewage treatment, which reduces the efficiency of the sewage treatment and decreases the quality of the receiving waters due to the pollutants that are contributed. The use of retention tanks constitutes a widely used way to mitigate this effect. However, the management of the pollutant loads encounters difficulties when the retention tanks are emptied. A new approach is proposed to solve this problem by fulfilling the treatment requirements in real time, focussing on the characteristics of the wastewater. The method is based on the execution of an Ant Colony Optimisation algorithm to obtain a satisfactory sequence for the discharge of the retention tanks. The discharge sequence considers the volume of stormwater and its concentration of pollutants including Suspended Solids, Biological Oxygen Demand and Chemical Oxygen Demand, Total Nitrogen and Total Phosphorus. The Ant Colony Optimisation algorithm was applied successfully to a case study with overall reduction of pollutant loads stored in retention tanks. The algorithm can be adapted in a simple way to the different scenarios, infrastructures and controllers of sewer systems. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Ant Colony Optimization for Control

    NARCIS (Netherlands)

    Van Ast, J.M.

    2010-01-01

    The very basis of this thesis is the collective behavior of ants in colonies. Ants are an excellent example of how rather simple behavior on a local level can lead to complex behavior on a global level that is beneficial for the individuals. The key in the self-organization of ants is communication

  5. Transfer function fitting using a continuous Ant Colony Optimization (ACO algorithm

    Directory of Open Access Journals (Sweden)

    A. Reineix

    2015-03-01

    Full Text Available An original approach is proposed in order to achieve the  fitting of ultra-wideband complex frequency functions, such  as the complex impedances, by using the so-called ACO  (Ant Colony Optimization methods. First, we present the  optimization principle of ACO, which originally was  dedicated to the combinatorial problems. Further on, the  extension to the continuous and mixed problems is  explained in more details. The interest in this approach is  proved by its ability to define practical constraints and  objectives, such as minimizing the number of filters used in  the model with respect to a fixed relative error. Finally, the  establishment of the model for the first and second order  filter types illustrates the power of the method and its  interest for the time-domain electromagnetic computation.

  6. A Novel Ant Colony Algorithm for the Single-Machine Total Weighted Tardiness Problem with Sequence Dependent Setup Times

    Directory of Open Access Journals (Sweden)

    Fardin Ahmadizar

    2011-08-01

    Full Text Available This paper deals with the NP-hard single-machine total weighted tardiness problem with sequence dependent setup times. Incorporating fuzzy sets and genetic operators, a novel ant colony optimization algorithm is developed for the problem. In the proposed algorithm, artificial ants construct solutions as orders of jobs based on the heuristic information as well as pheromone trails. To calculate the heuristic information, three well-known priority rules are adopted as fuzzy sets and then aggregated. When all artificial ants have terminated their constructions, genetic operators such as crossover and mutation are applied to generate new regions of the solution space. A local search is then performed to improve the performance quality of some of the solutions found. Moreover, at run-time the pheromone trails are locally as well as globally updated, and limited between lower and upper bounds. The proposed algorithm is experimented on a set of benchmark problems from the literature and compared with other metaheuristics.

  7. Solving the Traveling Salesman Problem Based on The Genetic Reactive Bone Route Algorithm whit Ant Colony System

    Directory of Open Access Journals (Sweden)

    Majid Yousefikhoshbakht

    2016-07-01

    Full Text Available The TSP is considered one of the most well-known combinatorial optimization tasks and researchers have paid so much attention to the TSP for many years. In this problem, a salesman starts to move from an arbitrary place called depot and after visits all of the nodes, finally comes back to the depot. The objective is to minimize the total distance traveled by the salesman.  Because this problem is a non-deterministic polynomial (NP-hard problem in nature, a hybrid meta-heuristic algorithm called REACSGA is used for solving the TSP. In REACSGA, a reactive bone route algorithm that uses the ant colony system (ACS for generating initial diversified solutions and the genetic algorithm (GA as an improved procedure are applied. Since the performance of the Metaheuristic algorithms is significantly influenced by their parameters, Taguchi Method is used to set the parameters of the proposed algorithm. The proposed algorithm is tested on several standard instances involving 24 to 318 nodes from the literature. The computational result shows that the results of the proposed algorithm are competitive with other metaheuristic algorithms for solving the TSP in terms of better quality of solution and computational time respectively. In addition, the proposed REACSGA is significantly efficient and finds closely the best known solutions for most of the instances in which thirteen best known solutions are also found.

  8. A universal optimization strategy for ant colony optimization algorithms based on the Physarum-inspired mathematical model

    International Nuclear Information System (INIS)

    Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao

    2014-01-01

    Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP. (paper)

  9. Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Young-Bo Sim

    2017-11-01

    Full Text Available In this paper, we proposed and developed Function-Oriented Networking (FON, a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV, which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.

  10. Three-Dimensional Path Planning and Guidance of Leg Vascular Based on Improved Ant Colony Algorithm in Augmented Reality.

    Science.gov (United States)

    Gao, Ming-ke; Chen, Yi-min; Liu, Quan; Huang, Chen; Li, Ze-yu; Zhang, Dian-hua

    2015-11-01

    Preoperative path planning plays a critical role in vascular access surgery. Vascular access surgery has superior difficulties and requires long training periods as well as precise operation. Yet doctors are on different leves, thus bulky size of blood vessels is usually chosen to undergo surgery and other possible optimal path is not considered. Moreover, patients and surgeons will suffer from X-ray radiation during the surgical procedure. The study proposed an improved ant colony algorithm to plan a vascular optimal three-dimensional path with overall consideration of factors such as catheter diameter, vascular length, diameter as well as the curvature and torsion. To protect the doctor and patient from exposing to X-ray long-term, the paper adopted augmented reality technology to register the reconstructed vascular model and physical model meanwhile, locate catheter by the electromagnetic tracking system and used Head Mounted Display to show the planning path in real time and monitor catheter push procedure. The experiment manifests reasonableness of preoperative path planning and proves the reliability of the algorithm. The augmented reality experiment real time and accurately displays the vascular phantom model, planning path and the catheter trajectory and proves the feasibility of this method. The paper presented a useful and feasible surgical scheme which was based on the improved ant colony algorithm to plan vascular three-dimensional path in augmented reality. The study possessed practical guiding significance in preoperative path planning, intraoperative catheter guiding and surgical training, which provided a theoretical method of path planning for vascular access surgery. It was a safe and reliable path planning approach and possessed practical reference value.

  11. A novel hybrid approach based on Particle Swarm Optimization and Ant Colony Algorithm to forecast energy demand of Turkey

    International Nuclear Information System (INIS)

    Kıran, Mustafa Servet; Özceylan, Eren; Gündüz, Mesut; Paksoy, Turan

    2012-01-01

    Highlights: ► PSO and ACO algorithms are hybridized for forecasting energy demands of Turkey. ► Linear and quadratic forms are developed to meet the fluctuations of indicators. ► GDP, population, export and import have significant impacts on energy demand. ► Quadratic form provides better fit solution than linear form. ► Proposed approach gives lower estimation error than ACO and PSO, separately. - Abstract: This paper proposes a new hybrid method (HAP) for estimating energy demand of Turkey using Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). Proposed energy demand model (HAPE) is the first model which integrates two mentioned meta-heuristic techniques. While, PSO, developed for solving continuous optimization problems, is a population based stochastic technique; ACO, simulating behaviors between nest and food source of real ants, is generally used for discrete optimizations. Hybrid method based PSO and ACO is developed to estimate energy demand using gross domestic product (GDP), population, import and export. HAPE is developed in two forms which are linear (HAPEL) and quadratic (HAPEQ). The future energy demand is estimated under different scenarios. In order to show the accuracy of the algorithm, a comparison is made with ACO and PSO which are developed for the same problem. According to obtained results, relative estimation errors of the HAPE model are the lowest of them and quadratic form (HAPEQ) provides better-fit solutions due to fluctuations of the socio-economic indicators.

  12. Complete Inverse Method Using Ant Colony Optimization Algorithm for Structural Parameters and Excitation Identification from Output Only Measurements

    Directory of Open Access Journals (Sweden)

    Jun Chen

    2014-01-01

    Full Text Available In vibration-based structural health monitoring of existing large civil structures, it is difficult, sometimes even impossible, to measure the actual excitation applied to structures. Therefore, an identification method using output-only measurements is crucial for the practical application of structural health monitoring. This paper integrates the ant colony optimization (ACO algorithm into the framework of the complete inverse method to simultaneously identify unknown structural parameters and input time history using output-only measurements. The complete inverse method, which was previously suggested by the authors, converts physical or spatial information of the unknown input into the objective function of an optimization problem that can be solved by the ACO algorithm. ACO is a newly developed swarm computation method that has a very good performance in solving complex global continuous optimization problems. The principles and implementation procedure of the ACO algorithm are first introduced followed by an introduction of the framework of the complete inverse method. Construction of the objective function is then described in detail with an emphasis on the common situation wherein a limited number of actuators are installed on some key locations of the structure. Applicability and feasibility of the proposed method were validated by numerical examples and experimental results from a three-story building model.

  13. Runtime analysis of the 1-ANT ant colony optimizer

    DEFF Research Database (Denmark)

    Doerr, Benjamin; Neumann, Frank; Sudholt, Dirk

    2011-01-01

    are investigated. The influence of the evaporation factor in the pheromone update mechanism and the robustness of this parameter w.r.t. the runtime behavior have been determined for the example function OneMax.This work puts forward the rigorous runtime analysis of the 1-ANT on the example functions Leading......The runtime analysis of randomized search heuristics is a growing field where, in the last two decades, many rigorous results have been obtained. First runtime analyses of ant colony optimization (ACO) have been conducted only recently. In these studies simple ACO algorithms such as the 1-ANT......Ones and BinVal. With respect to Evolutionary Algorithms (EAs), such analyses were essential to develop methods for the analysis on more complicated problems. The proof techniques required for the 1-ANT, unfortunately, differ significantly from those for EAs, which means that a new reservoir of methods has...

  14. Speed control of switched reluctance motor using genetic algorithm and ant colony based on optimizing PID controller

    Directory of Open Access Journals (Sweden)

    El-Sayed Ahmed Ibrahim Hassan

    2018-01-01

    Full Text Available Proportional-Integral-Derivative control is the most used kind of control which provides the simplest and most effective solution to different kinds of control engineering applications. But until now PID controller is poorly tuned in real life and online applications. While most of PID tuning is done manually. Switched reluctance motor (SRM has highly nonlinear characteristics since the developed/produced torque of the motor has a nonlinear function on both phase current and rotor position. These nonlinearities of the SRM drives make the conventional PID (proportional + integral + Derivative controller a poor choice for application where high dynamic performance is desired under all motor operating conditions. research paper comes up with two artificial and hybrid techniques involving Genetic Algorithm (GA and Ant Colony Optimization (ACO. Those techniques where used to tune the PID parameters for the switched reluctance motor (SRM and its performance were compared with the conventional method of “Ziegler Nichols. The results obtained reflects that, the use of those algorithms based controller improves the performance of the whole process in terms of a fast set point tracking and regulatory changes and also provides an optimum stability for the system itself with a minimum overshoot on the output signal.

  15. An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem

    Science.gov (United States)

    2015-01-01

    Genetic algorithms generate solutions for optimization problem based on theory of evolution using concepts such as reproduction, crossover and...the Darwin’s survival of fittest concept in the theory of evolution . The genetic algorithm search mechanism consists of three phases: (1) Evaluation

  16. Hybrid ANFIS with ant colony optimization algorithm for prediction of shear wave velocity from a carbonate reservoir in Iran

    Directory of Open Access Journals (Sweden)

    Hadi Fattahi

    2016-12-01

    Full Text Available Shear wave velocity (Vs data are key information for petrophysical, geophysical and geomechanical studies. Although compressional wave velocity (Vp measurements exist in almost all wells, shear wave velocity is not recorded for most of elderly wells due to lack of technologic tools. Furthermore, measurement of shear wave velocity is to some extent costly. This study proposes a novel methodology to remove aforementioned problems by use of hybrid adaptive neuro fuzzy inference system (ANFIS with ant colony optimization algorithm (ACO based on fuzzy c–means clustering (FCM and subtractive clustering (SCM. The ACO is combined with two ANFIS models for determining the optimal value of its user–defined parameters. The optimization implementation by the ACO significantly improves the generalization ability of the ANFIS models. These models are used in this study to formulate conventional well log data into Vs in a quick, cheap, and accurate manner. A total of 3030 data points was used for model construction and 833 data points were employed for assessment of ANFIS models. Finally, a comparison among ANFIS models, and six well–known empirical correlations demonstrated ANFIS models outperformed other methods. This strategy was successfully applied in the Marun reservoir, Iran.

  17. The modification of hybrid method of ant colony optimization, particle swarm optimization and 3-OPT algorithm in traveling salesman problem

    Science.gov (United States)

    Hertono, G. F.; Ubadah; Handari, B. D.

    2018-03-01

    The traveling salesman problem (TSP) is a famous problem in finding the shortest tour to visit every vertex exactly once, except the first vertex, given a set of vertices. This paper discusses three modification methods to solve TSP by combining Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) and 3-Opt Algorithm. The ACO is used to find the solution of TSP, in which the PSO is implemented to find the best value of parameters α and β that are used in ACO.In order to reduce the total of tour length from the feasible solution obtained by ACO, then the 3-Opt will be used. In the first modification, the 3-Opt is used to reduce the total tour length from the feasible solutions obtained at each iteration, meanwhile, as the second modification, 3-Opt is used to reduce the total tour length from the entire solution obtained at every iteration. In the third modification, 3-Opt is used to reduce the total tour length from different solutions obtained at each iteration. Results are tested using 6 benchmark problems taken from TSPLIB by calculating the relative error to the best known solution as well as the running time. Among those modifications, only the second and third modification give satisfactory results except the second one needs more execution time compare to the third modifications.

  18. Ant colony algorithm implementation in electron and photon Monte Carlo transport: Application to the commissioning of radiosurgery photon beams

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M.

    2010-01-01

    Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within ∼3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

  19. Ant colony algorithm implementation in electron and photon Monte Carlo transport: Application to the commissioning of radiosurgery photon beams

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S.; Galan, P.; Manzano, F.; Brualla, L.; Lallena, A. M. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' ' Carlos Haya' ' , Avda. Carlos Haya s/n, E-29010 Malaga (Spain); Unidad de Radiofisica Hospitalaria, Hospital Xanit Internacional, Avda. de los Argonautas s/n, E-29630 Benalmadena (Malaga) (Spain); NCTeam, Strahlenklinik, Universitaetsklinikum Essen, Hufelandstr. 55, D-45122 Essen (Germany); Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2010-07-15

    Purpose: In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators. Methods: The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map. Results: The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within {approx}3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field. Conclusions: The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

  20. Measuring activity in ant colonies

    Science.gov (United States)

    Noda, C.; Fernández, J.; Pérez-Penichet, C.; Altshuler, E.

    2006-12-01

    Ants, as paradigm of social insects, have become a recurrent example of efficient problem solvers via self-organization. In spite of the simple behavior of each individual, the colony as a whole displays "swarm intelligence:" the organization of ant trails for foraging is a typical output of it. But conventional techniques of observation can hardly record the amount of data needed to get a detailed understanding of self-organization of ant swarms in the wild. Here we are presenting a measurement system intended to monitor ant activity in the field comprising massive data acquisition and high sensitivity. A central role is played by an infrared sensor devised specifically to monitor relevant parameters to the activity of ants through the exits of the nest, although other sensors detecting temperature and luminosity are added to the system. We study the characteristics of the activity sensor and its performance in the field. Finally, we present massive data measured at one exit of a nest of Atta insularis, an ant endemic to Cuba, to illustrate the potential of our system.

  1. HYBRIDIZATION OF MODIFIED ANT COLONY OPTIMIZATION AND INTELLIGENT WATER DROPS ALGORITHM FOR JOB SCHEDULING IN COMPUTATIONAL GRID

    Directory of Open Access Journals (Sweden)

    P. Mathiyalagan

    2013-10-01

    Full Text Available As grid is a heterogeneous environment, finding an optimal schedule for the job is always a complex task. In this paper, a hybridization technique using intelligent water drops and Ant colony optimization which are nature-inspired swarm intelligence approaches are used to find the best resource for the job. Intelligent water drops involves in finding out all matching resources for the job requirements and the routing information (optimal path to reach those resources. Ant Colony optimization chooses the best resource among all matching resources for the job. The objective of this approach is to converge to the optimal schedule faster, minimize the make span of the job, improve load balancing of resources and efficient utilization of available resources.

  2. Using Improved Ant Colony Algorithm to Investigate EMU Circulation Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Yu Zhou

    2014-01-01

    Full Text Available High-speed railway is one of the most important ways to solve the long-standing travel difficulty problem in China. However, due to the high acquisition and maintenance cost, it is impossible for decision-making departments to purchase enough EMUs to satisfy the explosive travel demand. Therefore, there is an urgent need to study how to utilize EMU more efficiently and reduce costs in the case of completing a given task in train diagram. In this paper, an EMU circulation scheduling model is built based on train diagram constraints, maintenance constraints, and so forth; in the model solving process, an improved ACA algorithm has been designed. A case study is conducted to verify the feasibility of the model. Moreover, contrast tests have been carried out to compare the efficiency between the improved ACA and the traditional approaches. The results reveal that improved ACA method can solve the model with less time and the quality of each representative index is much better, which means that efficiency of the improved ACA method is higher and better scheduling scheme can be obtained.

  3. Edge detection in digital images using Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Marjan Kuchaki Rafsanjani

    2015-11-01

    Full Text Available Ant Colony Optimization (ACO is an optimization algorithm inspired by the behavior of real ant colonies to approximate the solutions of difficult optimization problems. In this paper, ACO is introduced to tackle the image edge detection problem. The proposed approach is based on the distribution of ants on an image; ants try to find possible edges by using a state transition function. Experimental results show that the proposed method compared to standard edge detectors is less sensitive to Gaussian noise and gives finer details and thinner edges when compared to earlier ant-based approaches.

  4. DESIGNING APPLICATION OF ANT COLONY SYSTEM ALGORITHM FOR THE SHORTEST ROUTE OF BANDA ACEH CITY AND ACEH BESAR REGENCY TOURISM BY USING GRAPHICAL USER INTERFACE MATLAB

    Directory of Open Access Journals (Sweden)

    Durisman Durisman

    2017-09-01

    Full Text Available Banda Aceh city and Aceh Besar Regency are two of the leading tourism areas located in the province of Aceh. For travelling, there are some important things to be considered, such as determining schedule and distance of tourism. Every tourist certainly chooses the shortest route to reach the destination since it can save time, energy, and money. The purpose of this reserach is to develop a method that can be used in calculating the shortest route and applied to the tourism of Banda Aceh city and Aceh Besar regency. In this reserach, Ant Colony Optimization algorithm is used to determine the shortest route to tourism of Banda Aceh city and Aceh Besar regency. From the analysis made by using both manual calculation and  GUI MATLAB program application test, the shortest route can be obtained with a minimum distance of 120.85 km in one travel. Based on the test result, the application for tourism (in Banda Aceh city and Aceh Besar regency shortest route searching built by utilizing the Ant Colony Optimization algorithm can find optimal route.  Keyword: tourism, the shortest route, Ant Colony Optimization

  5. Solving a Closed-Loop Location-Inventory-Routing Problem with Mixed Quality Defects Returns in E-Commerce by Hybrid Ant Colony Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Shuai Deng

    2016-01-01

    Full Text Available This paper presents a closed-loop location-inventory-routing problem model considering both quality defect returns and nondefect returns in e-commerce supply chain system. The objective is to minimize the total cost produced in both forward and reverse logistics networks. We propose a combined optimization algorithm named hybrid ant colony optimization algorithm (HACO to address this model that is an NP-hard problem. Our experimental results show that the proposed HACO is considerably efficient and effective in solving this model.

  6. Tuning PID Controller Using Multiobjective Ant Colony Optimization

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    Ibtissem Chiha

    2012-01-01

    Full Text Available This paper treats a tuning of PID controllers method using multiobjective ant colony optimization. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controllers (Kp, Ki, and Kd by minimizing the multiobjective function. The potential of using multiobjective ant algorithms is to identify the Pareto optimal solution. The other methods are applied to make comparisons between a classic approach based on the “Ziegler-Nichols” method and a metaheuristic approach based on the genetic algorithms. Simulation results demonstrate that the new tuning method using multiobjective ant colony optimization has a better control system performance compared with the classic approach and the genetic algorithms.

  7. Applying Ant Colony Algorithm and Neural Network Model to Color Deviation Defect Detection in Liquid Crystal Displays

    Directory of Open Access Journals (Sweden)

    Hong-Dar Lin

    2005-06-01

    Full Text Available Thin Film Transistor Liquid Crystal Display (TFT-LCD has excellent properties such as lower voltage to start and less occupied space if comparing with traditional Cathode-Ray Tube (CRT. But screen flaw points and display color deviation defects on image display exist in TFT-LCD products. This research proposes a new automated visual inspection method to solve the problems. We first use multivariate Hotelling T2 statistic for integrating coordinates of color models to construct a T2 energy diagram for inspecting defects and controlling patterns in TFT-LCD display images. An Ant Colony based approach that integrates computer vision techniques is developed to detect the flaw point defects. Then, Back Propagation Network (BPN model is proposed to inspect small deviation defects of the LCD display colors. Experimental results show the proposed system can provide good effects and practicality.

  8. Ant Colony Optimization and the Minimum Cut Problem

    DEFF Research Database (Denmark)

    Kötzing, Timo; Lehre, Per Kristian; Neumann, Frank

    2010-01-01

    Ant Colony Optimization (ACO) is a powerful metaheuristic for solving combinatorial optimization problems. With this paper we contribute to the theoretical understanding of this kind of algorithm by investigating the classical minimum cut problem. An ACO algorithm similar to the one that was proved...

  9. An Ant Colony Optimization algorithm for solving the fixed destination multi-depot multiple traveling salesman problem with non-random parameters

    Science.gov (United States)

    Ramadhani, T.; Hertono, G. F.; Handari, B. D.

    2017-07-01

    The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a single city (depot) will be determined. If there is more than one depot and salesmen start from and return to the same depot, then the problem is called Fixed Destination Multi-depot Multiple Traveling Salesman Problem (MMTSP). In this paper, MMTSP will be solved using the Ant Colony Optimization (ACO) algorithm. ACO is a metaheuristic optimization algorithm which is derived from the behavior of ants in finding the shortest route(s) from the anthill to a form of nourishment. In solving the MMTSP, the algorithm is observed with respect to different chosen cities as depots and non-randomly three parameters of MMTSP: m, K, L, those represents the number of salesmen, the fewest cities that must be visited by a salesman, and the most number of cities that can be visited by a salesman, respectively. The implementation is observed with four dataset from TSPLIB. The results show that the different chosen cities as depots and the three parameters of MMTSP, in which m is the most important parameter, affect the solution.

  10. Identification of gene knockout strategies using a hybrid of an ant colony optimization algorithm and flux balance analysis to optimize microbial strains.

    Science.gov (United States)

    Lu, Shi Jing; Salleh, Abdul Hakim Mohamed; Mohamad, Mohd Saberi; Deris, Safaai; Omatu, Sigeru; Yoshioka, Michifumi

    2014-09-28

    Reconstructions of genome-scale metabolic networks from different organisms have become popular in recent years. Metabolic engineering can simulate the reconstruction process to obtain desirable phenotypes. In previous studies, optimization algorithms have been implemented to identify the near-optimal sets of knockout genes for improving metabolite production. However, previous works contained premature convergence and the stop criteria were not clear for each case. Therefore, this study proposes an algorithm that is a hybrid of the ant colony optimization algorithm and flux balance analysis (ACOFBA) to predict near optimal sets of gene knockouts in an effort to maximize growth rates and the production of certain metabolites. Here, we present a case study that uses Baker's yeast, also known as Saccharomyces cerevisiae, as the model organism and target the rate of vanillin production for optimization. The results of this study are the growth rate of the model organism after gene deletion and a list of knockout genes. The ACOFBA algorithm was found to improve the yield of vanillin in terms of growth rate and production compared with the previous algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Fuzzy Rules for Ant Based Clustering Algorithm

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    Amira Hamdi

    2016-01-01

    Full Text Available This paper provides a new intelligent technique for semisupervised data clustering problem that combines the Ant System (AS algorithm with the fuzzy c-means (FCM clustering algorithm. Our proposed approach, called F-ASClass algorithm, is a distributed algorithm inspired by foraging behavior observed in ant colonyT. The ability of ants to find the shortest path forms the basis of our proposed approach. In the first step, several colonies of cooperating entities, called artificial ants, are used to find shortest paths in a complete graph that we called graph-data. The number of colonies used in F-ASClass is equal to the number of clusters in dataset. Hence, the partition matrix of dataset founded by artificial ants is given in the second step, to the fuzzy c-means technique in order to assign unclassified objects generated in the first step. The proposed approach is tested on artificial and real datasets, and its performance is compared with those of K-means, K-medoid, and FCM algorithms. Experimental section shows that F-ASClass performs better according to the error rate classification, accuracy, and separation index.

  12. Application of ant colony optimization in NPP classification fault location

    International Nuclear Information System (INIS)

    Xie Chunli; Liu Yongkuo; Xia Hong

    2009-01-01

    Nuclear Power Plant is a highly complex structural system with high safety requirements. Fault location appears to be particularly important to enhance its safety. Ant Colony Optimization is a new type of optimization algorithm, which is used in the fault location and classification of nuclear power plants in this paper. Taking the main coolant system of the first loop as the study object, using VB6.0 programming technology, the NPP fault location system is designed, and is tested against the related data in the literature. Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants. (authors)

  13. PARAMETER ESTIMATION OF VALVE STICTION USING ANT COLONY OPTIMIZATION

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    S. Kalaivani

    2012-07-01

    Full Text Available In this paper, a procedure for quantifying valve stiction in control loops based on ant colony optimization has been proposed. Pneumatic control valves are widely used in the process industry. The control valve contains non-linearities such as stiction, backlash, and deadband that in turn cause oscillations in the process output. Stiction is one of the long-standing problems and it is the most severe problem in the control valves. Thus the measurement data from an oscillating control loop can be used as a possible diagnostic signal to provide an estimate of the stiction magnitude. Quantification of control valve stiction is still a challenging issue. Prior to doing stiction detection and quantification, it is necessary to choose a suitable model structure to describe control-valve stiction. To understand the stiction phenomenon, the Stenman model is used. Ant Colony Optimization (ACO, an intelligent swarm algorithm, proves effective in various fields. The ACO algorithm is inspired from the natural trail following behaviour of ants. The parameters of the Stenman model are estimated using ant colony optimization, from the input-output data by minimizing the error between the actual stiction model output and the simulated stiction model output. Using ant colony optimization, Stenman model with known nonlinear structure and unknown parameters can be estimated.

  14. ADAPTIVE ANT COLONY OPTIMIZATION BASED GRADIENT FOR EDGE DETECTION

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    Febri Liantoni

    2014-08-01

    Full Text Available Ant Colony Optimization (ACO is a nature-inspired optimization algorithm which is motivated by ants foraging behavior. Due to its favorable advantages, ACO has been widely used to solve several NP-hard problems, including edge detection. Since ACO initially distributes ants at random, it may cause imbalance ant distribution which later affects path discovery process. In this paper an adaptive ACO is proposed to optimize edge detection by adaptively distributing ant according to gradient analysis. Ants are adaptively distributed according to gradient ratio of each image regions. Region which has bigger gradient ratio, will have bigger number of ant distribution. Experiments are conducted using images from various datasets. Precision and recall are used to quantitatively evaluate performance of the proposed algorithm. Precision and recall of adaptive ACO reaches 76.98 % and 96.8 %. Whereas highest precision and recall for standard ACO are 69.74 % and 74.85 %. Experimental results show that the adaptive ACO outperforms standard ACO which randomly distributes ants.

  15. Improved ant algorithms for software testing cases generation.

    Science.gov (United States)

    Yang, Shunkun; Man, Tianlong; Xu, Jiaqi

    2014-01-01

    Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to produce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations.

  16. Predicting Flood in Perlis Using Ant Colony Optimization

    International Nuclear Information System (INIS)

    Sabri, Syaidatul Nadia; Saian, Rizauddin

    2017-01-01

    Flood forecasting is widely being studied in order to reduce the effect of flood such as loss of property, loss of life and contamination of water supply. Usually flood occurs due to continuous heavy rainfall. This study used a variant of Ant Colony Optimization (ACO) algorithm named the Ant-Miner to develop the classification prediction model to predict flood. However, since Ant-Miner only accept discrete data, while rainfall data is a time series data, a pre-processing steps is needed to discretize the rainfall data initially. This study used a technique called the Symbolic Aggregate Approximation (SAX) to convert the rainfall time series data into discrete data. As an addition, Simple K-Means algorithm was used to cluster the data produced by SAX. The findings show that the predictive accuracy of the classification prediction model is more than 80%. (paper)

  17. Predicting Flood in Perlis Using Ant Colony Optimization

    Science.gov (United States)

    Nadia Sabri, Syaidatul; Saian, Rizauddin

    2017-06-01

    Flood forecasting is widely being studied in order to reduce the effect of flood such as loss of property, loss of life and contamination of water supply. Usually flood occurs due to continuous heavy rainfall. This study used a variant of Ant Colony Optimization (ACO) algorithm named the Ant-Miner to develop the classification prediction model to predict flood. However, since Ant-Miner only accept discrete data, while rainfall data is a time series data, a pre-processing steps is needed to discretize the rainfall data initially. This study used a technique called the Symbolic Aggregate Approximation (SAX) to convert the rainfall time series data into discrete data. As an addition, Simple K-Means algorithm was used to cluster the data produced by SAX. The findings show that the predictive accuracy of the classification prediction model is more than 80%.

  18. Ant colony optimization and constraint programming

    CERN Document Server

    Solnon, Christine

    2013-01-01

    Ant colony optimization is a metaheuristic which has been successfully applied to a wide range of combinatorial optimization problems. The author describes this metaheuristic and studies its efficiency for solving some hard combinatorial problems, with a specific focus on constraint programming. The text is organized into three parts. The first part introduces constraint programming, which provides high level features to declaratively model problems by means of constraints. It describes the main existing approaches for solving constraint satisfaction problems, including complete tree search

  19. Ant Larval Demand Reduces Aphid Colony Growth Rates in an Ant-Aphid Interaction

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    James M. Cook

    2012-02-01

    Full Text Available Ants often form mutualistic interactions with aphids, soliciting honeydew in return for protective services. Under certain circumstances, however, ants will prey upon aphids. In addition, in the presence of ants aphids may increase the quantity or quality of honeydew produced, which is costly. Through these mechanisms, ant attendance can reduce aphid colony growth rates. However, it is unknown whether demand from within the ant colony can affect the ant-aphid interaction. In a factorial experiment, we tested whether the presence of larvae in Lasius niger ant colonies affected the growth rate of Aphis fabae colonies. Other explanatory variables tested were the origin of ant colonies (two separate colonies were used and previous diet (sugar only or sugar and protein. We found that the presence of larvae in the ant colony significantly reduced the growth rate of aphid colonies. Previous diet and colony origin did not affect aphid colony growth rates. Our results suggest that ant colonies balance the flow of two separate resources from aphid colonies- renewable sugars or a protein-rich meal, depending on demand from ant larvae within the nest. Aphid payoffs from the ant-aphid interaction may change on a seasonal basis, as the demand from larvae within the ant colony waxes and wanes.

  20. Generating and prioritizing optimal paths using ant colony optimization

    Directory of Open Access Journals (Sweden)

    Mukesh Mann

    2015-03-01

    Full Text Available The assurance of software reliability partially depends on testing. Numbers of approaches for software testing are available with their proclaimed advantages and limitations, but accessibility of any one of them is a subject dependent. Time is a critical factor in deciding cost of any project. A deep insight has shown that executing test cases are time consuming and tedious activity. Thus stress has been given to develop algorithms which can suggest better pathways for testing. One such algorithm called Path Prioritization -Ant Colony Optimization (PP-ACO has been suggested in this paper which is inspired by real Ant's foraging behavior to generate optimal paths sequence of a decision to decision (DD path of a graph. The algorithm does full path coverage and suggests the best optimal sequences of path in path testing and prioritizes them according to path strength.

  1. A seismic fault recognition method based on ant colony optimization

    Science.gov (United States)

    Chen, Lei; Xiao, Chuangbai; Li, Xueliang; Wang, Zhenli; Huo, Shoudong

    2018-05-01

    Fault recognition is an important section in seismic interpretation and there are many methods for this technology, but no one can recognize fault exactly enough. For this problem, we proposed a new fault recognition method based on ant colony optimization which can locate fault precisely and extract fault from the seismic section. Firstly, seismic horizons are extracted by the connected component labeling algorithm; secondly, the fault location are decided according to the horizontal endpoints of each horizon; thirdly, the whole seismic section is divided into several rectangular blocks and the top and bottom endpoints of each rectangular block are considered as the nest and food respectively for the ant colony optimization algorithm. Besides that, the positive section is taken as an actual three dimensional terrain by using the seismic amplitude as a height. After that, the optimal route from nest to food calculated by the ant colony in each block is judged as a fault. Finally, extensive comparative tests were performed on the real seismic data. Availability and advancement of the proposed method were validated by the experimental results.

  2. Improving Emergency Management by Modeling Ant Colonies

    Science.gov (United States)

    2015-03-01

    neighboring cell than on the master plan, DNA .21 Johnson describes emergence as a means of self-organizing from the bottom-up. In emergent systems...carrying undesirable goods, such as bird poop, back to the nest. In the event poop makes it back to the nest, the poop is rejected near the entrance of the...by Army Ants,” 1124–5. 26 migrating to a colony raiding.98 A daily traffic jam is not indicative of organizational efficiency. Also, as the

  3. Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem

    Directory of Open Access Journals (Sweden)

    Baozhen Yao

    2014-02-01

    Full Text Available This paper deals with a real-life vehicle delivery routing problem, which is a seafood product delivery routing problem. Considering the features of the seafood product delivery routing problem, this paper formulated this problem as a multi-depot open vehicle routing problem. Since the multi-depot open vehicle routing problem is a very complex problem, a method is used to reduce the complexity of the problem by changing the multi-depot open vehicle routing problem into an open vehicle routing problem with a dummy central depot in this paper. Then, ant colony optimization is used to solve the problem. To improve the performance of the algorithm, crossover operation and some adaptive strategies are used. Finally, the computational results for the benchmark problems of the multi-depot vehicle routing problem indicate that the proposed ant colony optimization is an effective method to solve the multi-depot vehicle routing problem. Furthermore, the computation results of the seafood product delivery problem from Dalian, China also suggest that the proposed ant colony optimization is feasible to solve the seafood product delivery routing problem.

  4. Colony Fusion in a Parthenogenetic Ant, Pristomyrmex punctatus

    Science.gov (United States)

    Satow, Show; Satoh, Toshiyuki; Hirota, Tadao

    2013-01-01

    In the ant Pristomyrmex punctatus Smith (Hymenoptera: Formicidae), all young workers lay a small number of eggs parthenogenetically. Some colonies consist of monoclonal individuals that provide high inclusive fitness, according to the kin selection theory. However, in some populations, a majority of the colonies contain multiple lineages. Intracolonial genetic variation of parthenogenetic ants cannot be explained by the multiple mating of single founderesses or by the foundation of a colony by multiple foundresses, which are the usual causes of genetically diverse colonies in social insects. Here, we hypothesized that the fusion of established colonies might facilitate the formation of multiclonal colonies. Colony fusion decreases indirect benefits because of the reduction in intracolonial relatedness. However, when suitable nesting places for overwintering are scarce, colony fusion provides a strategy for the survival of colonies. Here, ants derived from different colonies were allowed to encounter one another in a container with just one nesting place. Initially, high aggression was observed; however, after several days, no aggression was observed and the ants shared the nest. When the fused colonies were allowed to transfer to two alternative nests, ants from different colonies occupied the same nest. This study highlights the importance of limiting the number of nesting places in order to understand the genetic diversity of parthenogenetic ant colonies. PMID:23895053

  5. Novel Degree Constrained Minimum Spanning Tree Algorithm Based on an Improved Multicolony Ant Algorithm

    Directory of Open Access Journals (Sweden)

    Xuemei Sun

    2015-01-01

    Full Text Available Degree constrained minimum spanning tree (DCMST refers to constructing a spanning tree of minimum weight in a complete graph with weights on edges while the degree of each node in the spanning tree is no more than d (d ≥ 2. The paper proposes an improved multicolony ant algorithm for degree constrained minimum spanning tree searching which enables independent search for optimal solutions among various colonies and achieving information exchanges between different colonies by information entropy. Local optimal algorithm is introduced to improve constructed spanning tree. Meanwhile, algorithm strategies in dynamic ant, random perturbations ant colony, and max-min ant system are adapted in this paper to optimize the proposed algorithm. Finally, multiple groups of experimental data show the superiority of the improved algorithm in solving the problems of degree constrained minimum spanning tree.

  6. Dual ant colony operational modal analysis parameter estimation method

    Science.gov (United States)

    Sitarz, Piotr; Powałka, Bartosz

    2018-01-01

    Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

  7. Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Haitao Xu

    2018-01-01

    Full Text Available As we all know, there are a great number of optimization problems in the world. One of the relatively complicated and high-level problems is the vehicle routing problem (VRP. Dynamic vehicle routing problem (DVRP is a major variant of VRP, and it is closer to real logistic scene. In DVRP, the customers’ demands appear with time, and the unserved customers’ points must be updated and rearranged while carrying out the programming paths. Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades. In this paper, we have two main contributions to solving DVRP. Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO, which is the traditional Ant Colony Optimization (ACO fusing improved K-means and crossover operation. K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely. Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method. In the experiment, the results for different scale problems are compared to those of previously published papers. Experimental results show that the algorithm is feasible and efficient.

  8. Effective ANT based Routing Algorithm for Data Replication in MANETs

    Directory of Open Access Journals (Sweden)

    N.J. Nithya Nandhini

    2013-12-01

    Full Text Available In mobile ad hoc network, the nodes often move and keep on change its topology. Data packets can be forwarded from one node to another on demand. To increase the data accessibility data are replicated at nodes and made as sharable to other nodes. Assuming that all mobile host cooperative to share their memory and allow forwarding the data packets. But in reality, all nodes do not share the resources for the benefits of others. These nodes may act selfishly to share memory and to forward the data packets. This paper focuses on selfishness of mobile nodes in replica allocation and routing protocol based on Ant colony algorithm to improve the efficiency. The Ant colony algorithm is used to reduce the overhead in the mobile network, so that it is more efficient to access the data than with other routing protocols. This result shows the efficiency of ant based routing algorithm in the replication allocation.

  9. Comprehensive Evaluation for Operating Efficiency of Electricity Retail Companies Based on the Improved TOPSIS Method and LSSVM Optimized by Modified Ant Colony Algorithm from the View of Sustainable Development

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2018-03-01

    Full Text Available The electricity market of China is currently in the process of a new institutional reform. Diversified electricity retail entities are gradually being established with the opening of the marketing electricity side. In the face of a complex market environment and fierce competition, the operating efficiency can directly reflect the current market position and development of electricity retail companies. TOPSIS method can make full use of the information of original data, calculate the distance between evaluated objects and the ideal solutions and get the relative proximity, which is generally used in the overall department and comprehensive evaluation of the benefits. Least squares support vector machine (LSSVM, with high convergence precision, helps save the training time of algorithm by solving linear equations and is used to predict the comprehensive evaluation value. Considering the ultimate goal of sustainable development, a comprehensive evaluation model on operating efficiency of electricity retail companies based on the improved TOPSIS method and LSSVM optimized by modified ant colony algorithm is proposed in this paper. Firstly, from the view of sustainable development, an operating efficiency evaluation indicator system is constructed. Secondly, the entropy weight method is applied to empower the indicators objectively. After that, based on the improved TOPSIS method, the reverse problem in the evaluation process is eliminated. According to the relative proximity between the evaluated objects and the absolute ideal solutions, the scores of comprehensive evaluation for operating efficiency can then be ranked. Finally, the LSSVM optimized by modified ant colony algorithm is introduced to realize the simplified expert scoring process and fast calculation in the comprehensive evaluation process, and its improved learning and generalization ability can be used in the comprehensive evaluation of similar projects. The example analysis proves

  10. The adaptive significance of phasic colony cycles in army ants.

    Science.gov (United States)

    Garnier, Simon; Kronauer, Daniel J C

    2017-09-07

    Army ants are top arthropod predators in tropical forests around the world. The colonies of many army ant species undergo stereotypical behavioral and reproductive cycles, alternating between brood care and reproductive phases. In the brood care phase, colonies contain a cohort of larvae that are synchronized in their development and have to be fed. In the reproductive phase larvae are absent and oviposition takes place. Despite these colony cycles being a striking feature of army ant biology, their adaptive significance is unclear. Here we use a modeling approach to show that cyclic reproduction is favored under conditions where per capita foraging costs decrease with the number of larvae in a colony ("High Cost of Entry" scenario), while continuous reproduction is favored under conditions where per capita foraging costs increase with the number of larvae ("Resource Exhaustion" scenario). We argue that the former scenario specifically applies to army ants, because large raiding parties are required to overpower prey colonies. However, once raiding is successful it provides abundant food for a large cohort of larvae. The latter scenario, on the other hand, will apply to non-army ants, because in those species local resource depletion will force workers to forage over larger distances to feed large larval cohorts. Our model provides a quantitative framework for understanding the adaptive value of phasic colony cycles in ants. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Aircraft technology portfolio optimization using ant colony optimization

    Science.gov (United States)

    Villeneuve, Frederic J.; Mavris, Dimitri N.

    2012-11-01

    Technology portfolio selection is a combinatorial optimization problem often faced with a large number of combinations and technology incompatibilities. The main research question addressed in this article is to determine if Ant Colony Optimization (ACO) is better suited than Genetic Algorithms (GAs) and Simulated Annealing (SA) for technology portfolio optimization when incompatibility constraints between technologies are present. Convergence rate, capability to find optima, and efficiency in handling of incompatibilities are the three criteria of comparison. The application problem consists of finding the best technology portfolio from 29 aircraft technologies. The results show that ACO and GAs converge faster and find optima more easily than SA, and that ACO can optimize portfolios with technology incompatibilities without using penalty functions. This latter finding paves the way for more use of ACO when the number of constraints increases, such as in the technology and concept selection for complex engineering systems.

  12. Model for social interaction, competition and dominance in ant colonies

    Science.gov (United States)

    Anggriani, N.; Aryani, I.; Darmawati, Supriatna, A. K.

    2014-02-01

    It has been known that characteristic of social life within ant colonies includes efficient class division, harmonious appearance, but also competition within nestmates. Conflict between queens, male and female labors frequently occurs due to different interest among class members. A mathematical model for interaction between queens, male and female workers in ant colonies is discussed here. Interesting phenomena such as male-male competition and queen dominance are analyzed and stable coexistence is shown. It is also shown that heavy competition is even necessary to maintain a certain level of coexistence in the colonies.

  13. Runtime analysis of ant colony optimization on dynamic shortest path problems

    DEFF Research Database (Denmark)

    Lissovoi, Andrei; Witt, Carsten

    2013-01-01

    A simple ACO algorithm called λ-MMAS for dynamic variants of the single-destination shortest paths problem is studied by rigorous runtime analyses. Building upon previous results for the special case of 1-MMAS, it is studied to what extent an enlarged colony using $\\lambda$ ants per vertex helps ...

  14. Runtime analysis of ant colony optimization on dynamic shortest path problems

    DEFF Research Database (Denmark)

    Lissovoi, Andrei; Witt, Carsten

    2015-01-01

    A simple ACO algorithm called lambda-MMAS for dynamic variants of the single-destination shortest paths problem is studied by rigorous runtime analyses. Building upon previous results for the special case of 1-MMAS, it is studied to what extent an enlarged colony using lambda ants per vertex help...

  15. Multi-view 3D scene reconstruction using ant colony optimization techniques

    International Nuclear Information System (INIS)

    Chrysostomou, Dimitrios; Gasteratos, Antonios; Nalpantidis, Lazaros; Sirakoulis, Georgios C

    2012-01-01

    This paper presents a new method performing high-quality 3D object reconstruction of complex shapes derived from multiple, calibrated photographs of the same scene. The novelty of this research is found in two basic elements, namely: (i) a novel voxel dissimilarity measure, which accommodates the elimination of the lighting variations of the models and (ii) the use of an ant colony approach for further refinement of the final 3D models. The proposed reconstruction procedure employs a volumetric method based on a novel projection test for the production of a visual hull. While the presented algorithm shares certain aspects with the space carving algorithm, it is, nevertheless, first enhanced with the lightness compensating image comparison method, and then refined using ant colony optimization. The algorithm is fast, computationally simple and results in accurate representations of the input scenes. In addition, compared to previous publications, the particular nature of the proposed algorithm allows accurate 3D volumetric measurements under demanding lighting environmental conditions, due to the fact that it can cope with uneven light scenes, resulting from the characteristics of the voxel dissimilarity measure applied. Besides, the intelligent behavior of the ant colony framework provides the opportunity to formulate the process as a combinatorial optimization problem, which can then be solved by means of a colony of cooperating artificial ants, resulting in very promising results. The method is validated with several real datasets, along with qualitative comparisons with other state-of-the-art 3D reconstruction techniques, following the Middlebury benchmark. (paper)

  16. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

    Directory of Open Access Journals (Sweden)

    Thenmozhi Srinivasan

    2015-01-01

    Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.

  17. Ant colony optimization for solving university facility layout problem

    Science.gov (United States)

    Mohd Jani, Nurul Hafiza; Mohd Radzi, Nor Haizan; Ngadiman, Mohd Salihin

    2013-04-01

    Quadratic Assignment Problems (QAP) is classified as the NP hard problem. It has been used to model a lot of problem in several areas such as operational research, combinatorial data analysis and also parallel and distributed computing, optimization problem such as graph portioning and Travel Salesman Problem (TSP). In the literature, researcher use exact algorithm, heuristics algorithm and metaheuristic approaches to solve QAP problem. QAP is largely applied in facility layout problem (FLP). In this paper we used QAP to model university facility layout problem. There are 8 facilities that need to be assigned to 8 locations. Hence we have modeled a QAP problem with n ≤ 10 and developed an Ant Colony Optimization (ACO) algorithm to solve the university facility layout problem. The objective is to assign n facilities to n locations such that the minimum product of flows and distances is obtained. Flow is the movement from one to another facility, whereas distance is the distance between one locations of a facility to other facilities locations. The objective of the QAP is to obtain minimum total walking (flow) of lecturers from one destination to another (distance).

  18. Using pleometrosis (multiple queens) and pupae transplantation to boost weaver ant (Oecophylla smaragdina) colony growth in ant nurseries

    DEFF Research Database (Denmark)

    Offenberg, Hans Joachim; Nielsen, Mogens Gissel; Peng, Renkang

    2011-01-01

    Weaver ants (Oecophylla spp.) are increasingly being used for biocontrol and are targeted for future production of insect protein in ant farms. An efficient production of live ant colonies may facilitate the utilization of these ants but the production of mature colonies is hampered by the long t...

  19. Hierarchy length in orphaned colonies of the ant Temnothorax nylanderi

    Science.gov (United States)

    Heinze, J.

    2008-08-01

    Workers of the ant Temnothorax nylanderi form dominance orders in orphaned colonies in which only one or a few top-ranking workers begin to produce males from unfertilized eggs. Between one and 11 individuals initiated 80% of all aggression in 14 queenless colonies. As predicted from inclusive fitness models (Molet M, van Baalen M, Monnin T, Insectes Soc 52:247 256, 2005), hierarchy length was found to first increase with colony size and then to level off at larger worker numbers. The frequency and skew of aggression decreased with increasing size, indicating that rank orders are less pronounced in larger colonies.

  20. Optimizing Robinson Operator with Ant Colony Optimization As a Digital Image Edge Detection Method

    Science.gov (United States)

    Yanti Nasution, Tarida; Zarlis, Muhammad; K. M Nasution, Mahyuddin

    2017-12-01

    Edge detection serves to identify the boundaries of an object against a background of mutual overlap. One of the classic method for edge detection is operator Robinson. Operator Robinson produces a thin, not assertive and grey line edge. To overcome these deficiencies, the proposed improvements to edge detection method with the approach graph with Ant Colony Optimization algorithm. The repairs may be performed are thicken the edge and connect the edges cut off. Edge detection research aims to do optimization of operator Robinson with Ant Colony Optimization then compare the output and generated the inferred extent of Ant Colony Optimization can improve result of edge detection that has not been optimized and improve the accuracy of the results of Robinson edge detection. The parameters used in performance measurement of edge detection are morphology of the resulting edge line, MSE and PSNR. The result showed that Robinson and Ant Colony Optimization method produces images with a more assertive and thick edge. Ant Colony Optimization method is able to be used as a method for optimizing operator Robinson by improving the image result of Robinson detection average 16.77 % than classic Robinson result.

  1. Ant Colony Optimization ACO For The Traveling Salesman Problem TSP Using Partitioning

    Directory of Open Access Journals (Sweden)

    Alok Bajpai

    2015-08-01

    Full Text Available Abstract An ant colony optimization is a technique which was introduced in 1990s and which can be applied to a variety of discrete combinatorial optimization problem and to continuous optimization. The ACO algorithm is simulated with the foraging behavior of the real ants to find the incremental solution constructions and to realize a pheromone laying-and-following mechanism. This pheromone is the indirect communication among the ants. In this paper we introduces the partitioning technique based on the divide and conquer strategy for the traveling salesman problem which is one of the most important combinatorial problem in which the original problem is partitioned into the group of sub problems. And then we apply the ant colony algorithm using candidate list strategy for each smaller sub problems. After that by applying the local optimization and combining the sub problems to find the good solution for the original problem by improving the exploration efficiency of the ants. At the end of this paper we have also be presented the comparison of result with the normal ant colony system for finding the optimal solution to the traveling salesman problem.

  2. Clarifying Cutting and Sewing Processes with Due Windows Using an Effective Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Rong-Hwa Huang

    2013-01-01

    Full Text Available The cutting and sewing process is a traditional flow shop scheduling problem in the real world. This two-stage flexible flow shop is often commonly associated with manufacturing in the fashion and textiles industry. Many investigations have demonstrated that the ant colony optimization (ACO algorithm is effective and efficient for solving scheduling problems. This work applies a novel effective ant colony optimization (EACO algorithm to solve two-stage flexible flow shop scheduling problems and thereby minimize earliness, tardiness, and makespan. Computational results reveal that for both small and large problems, EACO is more effective and robust than both the particle swarm optimization (PSO algorithm and the ACO algorithm. Importantly, this work demonstrates that EACO can solve complex scheduling problems in an acceptable period of time.

  3. Dynamic Network Formation Using Ant Colony Optimization

    Science.gov (United States)

    2009-03-01

    Problem (DVRP) ............................................ 36 2.7.2 Dynamic Traveling Salesman Problem (DTSP) ....................................... 41...47 2.8.3 Distributed Traveling Salesman Problem ................................................. 48 2.8.4 FIRE Ant...uses the fixed cost of the network in its calculation and commodities are not included in the problem formulation . Using a probabilistic undirected

  4. Reliability optimization using multiobjective ant colony system approaches

    International Nuclear Information System (INIS)

    Zhao Jianhua; Liu Zhaoheng; Dao, M.-T.

    2007-01-01

    The multiobjective ant colony system (ACS) meta-heuristic has been developed to provide solutions for the reliability optimization problem of series-parallel systems. This type of problems involves selection of components with multiple choices and redundancy levels that produce maximum benefits, and is subject to the cost and weight constraints at the system level. These are very common and realistic problems encountered in conceptual design of many engineering systems. It is becoming increasingly important to develop efficient solutions to these problems because many mechanical and electrical systems are becoming more complex, even as development schedules get shorter and reliability requirements become very stringent. The multiobjective ACS algorithm offers distinct advantages to these problems compared with alternative optimization methods, and can be applied to a more diverse problem domain with respect to the type or size of the problems. Through the combination of probabilistic search, multiobjective formulation of local moves and the dynamic penalty method, the multiobjective ACSRAP, allows us to obtain an optimal design solution very frequently and more quickly than with some other heuristic approaches. The proposed algorithm was successfully applied to an engineering design problem of gearbox with multiple stages

  5. Ant-cuckoo colony optimization for feature selection in digital mammogram.

    Science.gov (United States)

    Jona, J B; Nagaveni, N

    2014-01-15

    Digital mammogram is the only effective screening method to detect the breast cancer. Gray Level Co-occurrence Matrix (GLCM) textural features are extracted from the mammogram. All the features are not essential to detect the mammogram. Therefore identifying the relevant feature is the aim of this work. Feature selection improves the classification rate and accuracy of any classifier. In this study, a new hybrid metaheuristic named Ant-Cuckoo Colony Optimization a hybrid of Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for feature selection in Digital Mammogram. ACO is a good metaheuristic optimization technique but the drawback of this algorithm is that the ant will walk through the path where the pheromone density is high which makes the whole process slow hence CS is employed to carry out the local search of ACO. Support Vector Machine (SVM) classifier with Radial Basis Kernal Function (RBF) is done along with the ACO to classify the normal mammogram from the abnormal mammogram. Experiments are conducted in miniMIAS database. The performance of the new hybrid algorithm is compared with the ACO and PSO algorithm. The results show that the hybrid Ant-Cuckoo Colony Optimization algorithm is more accurate than the other techniques.

  6. Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

    Directory of Open Access Journals (Sweden)

    Peng Lin

    2014-01-01

    Full Text Available A dam ant colony optimization (D-ACO analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline.

  7. Application of ant colony optimisation in distribution transformer sizing

    African Journals Online (AJOL)

    This study proposes an optimisation method for transformer sizing in power system using ant colony optimisation and a verification of the process by MATLAB software. The aim is to address the issue of transformer sizing which is a major challenge affecting its effective performance, longevity, huge capital cost and power ...

  8. application of ant colony optimisation in distribution transformer sizing

    African Journals Online (AJOL)

    HP

    This study proposes an optimisation method for transformer sizing in power system using ant colony optimisation and a verification of the process by MATLAB software. The aim is to address the issue of transformer sizing which is a major challenge affecting its effective performance, longevity, huge capital cost and power ...

  9. Improved ant Colony Optimization for Virtual Teams Building in Collaborative Process Planning

    Directory of Open Access Journals (Sweden)

    Yingying Su

    2014-02-01

    Full Text Available Virtual teams have been adopted by organizations to gain competitive advantages in this global economy. Virtual teams are a ubiquitous part of getting work done in almost every organization. For the purpose of building virtual teams in collaborative process planning, the method based on improved ant colony algorithm (IMACO was proposed. The concept of virtual team was illustrated and the necessity of building virtual teams in collaborative process planning was analyzed. The sub tasks with certain timing relationship were described and the model of building virtual teams in collaborative process planning was established, which was solved by improved ant colony algorithm. In this paper applications of the IMACO and ACO are compared and demonstrate that the use of the IMACO algorithm performs better. An example was studied to illustrate the effectiveness of the strategy.

  10. Multi-Robot Dynamic Task Allocation Using Modified Ant Colony System

    Science.gov (United States)

    Xu, Zhenzhen; Xia, Feng; Zhang, Xianchao

    This paper presents a dynamic task allocation algorithm for multiple robots to visit multiple targets. This algorithm is specifically designed for the environment where robots have dissimilar starting and ending locations. And the constraint of balancing the number of targets visited by each robot is considered. More importantly, this paper takes into account the dynamicity of multi-robot system and the obstacles in the environment. This problem is modeled as a constrained MTSP which can not be transformed to TSP and can not be solved by classical Ant Colony System (ACS). The Modified Ant Colony System (MACS) is presented to solve this problem and the unvisited targets are allocated to appropriate robots dynamically. The simulation results show that the output of the proposed algorithm can satisfy the constraints and dynamicity for the problem of multi-robot task allocation.

  11. Ant colony system (ACS with hybrid local search to solve vehicle routing problems

    Directory of Open Access Journals (Sweden)

    Suphan Sodsoon

    2016-02-01

    Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.

  12. Applying Data Clustering Feature to Speed Up Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Chao-Yang Pang

    2014-01-01

    Full Text Available Ant colony optimization (ACO is often used to solve optimization problems, such as traveling salesman problem (TSP. When it is applied to TSP, its runtime is proportional to the squared size of problem N so as to look less efficient. The following statistical feature is observed during the authors’ long-term gene data analysis using ACO: when the data size N becomes big, local clustering appears frequently. That is, some data cluster tightly in a small area and form a class, and the correlation between different classes is weak. And this feature makes the idea of divide and rule feasible for the estimate of solution of TSP. In this paper an improved ACO algorithm is presented, which firstly divided all data into local clusters and calculated small TSP routes and then assembled a big TSP route with them. Simulation shows that the presented method improves the running speed of ACO by 200 factors under the condition that data set holds feature of local clustering.

  13. DIDS Using Cooperative Agents Based on Ant Colony Clustering

    Directory of Open Access Journals (Sweden)

    Muhammad Nur Kholish Abdurrazaq

    2015-07-01

    Full Text Available Intrusion detection systems (IDS play an important role in information security. Two major problems in the development of IDSs are the computational aspect and the architectural aspect. The computational or algorithmic problems include lacking ability of novel-attack detection and computation overload caused by large data traffic. The architectural problems are related to the communication between components of detection, including difficulties to overcome distributed and coordinated attacks because of the need of large amounts of distributed information and synchronization between detection components. This paper proposes a multi-agent architecture for a distributed intrusion detection system (DIDS based on ant-colony clustering (ACC, for recognizing new and coordinated attacks, handling large data traffic, synchronization, co-operation between components without the presence of centralized computation, and good detection performance in real-time with immediate alarm notification. Feature selection based on principal component analysis (PCA is used for dimensional reduction of NSL-KDD. Initial features are transformed to new features in smaller dimensions, where probing attacks (Ra-Probe have a characteristic sign in their average value that is different from that of normal activity. Selection is based on the characteristics of these factors, resulting in a two-dimensional subset of the 75% data reduction.

  14. Emigration of a colony of the leaf-cutting ant Acromyrmex heyeri Forel (Hymenoptera, Formicidae

    Directory of Open Access Journals (Sweden)

    Mariane Aparecida Nickele

    2012-09-01

    Full Text Available Emigration of a colony of the leaf-cutting ant Acromyrmex heyeri Forel (Hymenoptera, Formicidae. Colony migration is a poorly studied phenomenon in leaf-cutting ants. Here we report on the emigration of a colony of the leaf-cutting ant A. heyeri in Brazil. The colony emigrated to a new location 47.4 m away from the original nest site, possibly because it had undergone considerable stress due to competitive interactions with a colony of Acromyrmex crassispinus.

  15. Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

    Directory of Open Access Journals (Sweden)

    Kalinowski Krzysztof

    2017-01-01

    Full Text Available The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.. Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.

  16. An element search ant colony technique for solving virtual machine placement problem

    Science.gov (United States)

    Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

    2017-09-01

    The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

  17. An approach using quantum ant colony optimization applied to the problem of identification of nuclear power plant transients

    International Nuclear Information System (INIS)

    Silva, Marcio H.; Schirru, Roberto; Medeiros, Jose A.C.C.

    2009-01-01

    Using concepts and principles of the quantum computation, as the quantum bit and superposition of states, coupled with the biological metaphor of a colony of ants, used in the Ant Colony Optimization algorithm (ACO), Wang et al developed the Quantum Ant Colony Optimization (QACO). In this paper we present a modification of the algorithm proposed by Wang et al. While the original QACO was used just for simple benchmarks functions with, at the most, two dimensions, QACO A lfa was developed for application where the original QACO, due to its tendency to converge prematurely, does not obtain good results, as in complex multidimensional functions. Furthermore, to evaluate its behavior, both algorithms are applied to the real problem of identification of accidents in PWR nuclear power plants. (author)

  18. Ant colonies prefer infected over uninfected nest sites

    DEFF Research Database (Denmark)

    Pontieri, Luigi; Vojvodic, Svjetlana; Graham, Riley

    2014-01-01

    During colony relocation, the selection of a new nest involves exploration and assessment of potential sites followed by colony movement on the basis of a collective decision making process. Hygiene and pathogen load of the potential nest sites are factors worker scouts might evaluate, given...... the high risk of epidemics in group-living animals. Choosing nest sites free of pathogens is hypothesized to be highly efficient in invasive ants as each of their introduced populations is often an open network of nests exchanging individuals (unicolonial) with frequent relocation into new nest sites...... and low genetic diversity, likely making these species particularly vulnerable to parasites and diseases. We investigated the nest site preference of the invasive pharaoh ant, Monomorium pharaonis, through binary choice tests between three nest types: nests containing dead nestmates overgrown...

  19. Response Ant Colony Optimization of End Milling Surface Roughness

    Directory of Open Access Journals (Sweden)

    Ahmed N. Abd Alla

    2010-03-01

    Full Text Available Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6 with Response Ant Colony Optimization (RACO. The approach is based on Response Surface Method (RSM and Ant Colony Optimization (ACO. The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth. The first order model indicates that the feedrate is the most significant factor affecting surface roughness.

  20. Ant colony optimization approach to estimate energy demand of Turkey

    International Nuclear Information System (INIS)

    Duran Toksari, M.

    2007-01-01

    This paper attempts to shed light on the determinants of energy demand in Turkey. Energy demand model is first proposed using the ant colony optimization (ACO) approach. It is multi-agent systems in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. ACO energy demand estimation (ACOEDE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear and quadratic. Quadratic A COEDE provided better-fit solution due to fluctuations of the economic indicators. The ACOEDE model plans the energy demand of Turkey until 2025 according to three scenarios. The relative estimation errors of the ACOEDE model are the lowest when they are compared with the Ministry of Energy and Natural Resources (MENR) projection

  1. Intelligent Hypothermia Care System using AntColony Optimization for Rules Prediction

    Directory of Open Access Journals (Sweden)

    Hayder Naser Khraibet

    2017-12-01

    Full Text Available Intelligent Hypothermia Care System (IHCS is an intelligence system uses set of methodologies, algorithms, architectures and processes to determine where patients in a postoperative recovery area must be sent. Hypothermia is a significant concern after surgery. This paper utilizes the classification task in data mining to propose an intelligent technique to predict where to send a patient after surgery: intensive care unit, general floor or home. To achieve this goal, this paper evaluates the performance of decision tree algorithm, exemplifying the deterministic approach, against the AntMiner algorithm, exemplifying the heuristic approach, to choose the best approach in detecting the patient’s status. Results show the outperformance of the heuristic approach. The implication of this proposal will be twofold: in hypothermia treatment and in the application of ant colony optimization

  2. Dealing with water deficit in Atta ant colonies: large ants scout for water while small ants transport it

    Directory of Open Access Journals (Sweden)

    Antonio Carlos Da-Silva

    2012-07-01

    Leafcutter ants (Atta sexdens rubropilosa (Forel 1908 have an elaborate social organization, complete with caste divisions. Activities carried out by specialist groups contribute to the overall success and survival of the colony when it is confronted with environmental challenges such as dehydration. Ants detect variations in humidity inside the nest and react by activating several types of behavior that enhance water uptake and decrease water loss, but it is not clear whether or not a single caste collects water regardless of the cost of bringing this resource back to the colony. Accordingly, we investigated water collection activities in three colonies of Atta sexdens rubropilosa experimentally exposed to water stress. Specifically, we analyzed whether or not the same ant caste foraged for water, regardless of the absolute energetic cost (distance of transporting this resource back to the colony. Our experimental design offered water sources at 0 m, 1 m and 10 m from the nest. We studied the body size of ants near the water sources from the initial offer of water (time  =  0 to 120 min, and tested for specialization. We observed a reduction in the average size and variance of ants that corroborated the specialization hypothesis. Although the temporal course of specialization changed with distance, the final outcome was similar among distances. Thus, we conclude that, for this species, a specialist (our use of the word “specialist” does not mean exclusive task force is responsible for collecting water, regardless of the cost of transporting water back to the colony.

  3. Ant colony optimization techniques for the hamiltonian p-median problem

    Directory of Open Access Journals (Sweden)

    M. Zohrehbandian

    2010-12-01

    Full Text Available Location-Routing problems involve locating a number of facilitiesamong candidate sites and establishing delivery routes to a set of users in such a way that the total system cost is minimized. A special case of these problems is Hamiltonian p-Median problem (HpMP. This research applies the metaheuristic method of ant colony optimization (ACO to solve the HpMP. Modifications are made to the ACO algorithm used to solve the traditional vehicle routing problem (VRP in order to allow the search of the optimal solution of the HpMP. Regarding this metaheuristic algorithm a computational experiment is reported as well.

  4. JOB SHOP METHODOLOGY BASED ON AN ANT COLONY

    Directory of Open Access Journals (Sweden)

    OMAR CASTRILLON

    2009-01-01

    Full Text Available The purpose of this study is to reduce the total process time (Makespan and to increase the machines working time, in a job shop environment, using a heuristic based on ant colony optimization. This work is developed in two phases: The first stage describes the identification and definition of heuristics for the sequential processes in the job shop. The second stage shows the effectiveness of the system in the traditional programming of production. A good solution, with 99% efficiency is found using this technique.

  5. ACCURACY Detection of Digital Image Forgery by Using Ant Colony Optimization Technique

    Directory of Open Access Journals (Sweden)

    Singh Sarvjit

    2016-01-01

    Full Text Available Image forgery is one of the well known fields in which researches continuously exploring new areas. In digital image forgery one can change image in many ways using several software’s, researchers exploring new algorithms to detect image forgery areas and change it to original pixel values if possible. In this paper we employed ACO (Ant Colony Optimization to find areas which are manipulated with some software. The experimental results prove that ACO is better than existing methods of detecting tampered regions in digital photo images.

  6. A nuclear reactor core fuel reload optimization using artificial ant colony connective networks

    Energy Technology Data Exchange (ETDEWEB)

    Lima, Alan M.M. de [Universidade Federal do Rio de Janeiro, PEN/COPPE - UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: alanmmlima@yahoo.com.br; Schirru, Roberto [Universidade Federal do Rio de Janeiro, PEN/COPPE - UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: schirru@lmp.ufrj.br; Carvalho da Silva, Fernando [Universidade Federal do Rio de Janeiro, PEN/COPPE - UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: fernando@con.ufrj.br; Medeiros, Jose Antonio Carlos Canedo [Universidade Federal do Rio de Janeiro, PEN/COPPE - UFRJ, Ilha do Fundao s/n, CEP 21945-970 Rio de Janeiro (Brazil)], E-mail: canedo@lmp.ufrj.br

    2008-09-15

    The core of a nuclear Pressurized Water Reactor (PWR) may be reloaded every time the fuel burn-up is such that it is not more possible to maintain the reactor operating at nominal power. The nuclear core fuel reload optimization problem consists in finding a pattern of burned-up and fresh-fuel assemblies that maximize the number of full operational days. This is an NP-Hard problem, meaning that complexity grows exponentially with the number of fuel assemblies in the core. Moreover, the problem is non-linear and its search space is highly discontinuous and multi-modal. Ant Colony System (ACS) is an optimization algorithm based on artificial ants that uses the reinforcement learning technique. The ACS was originally developed to solve the Traveling Salesman Problem (TSP), which is conceptually similar to the nuclear core fuel reload problem. In this work a parallel computational system based on the ACS, called Artificial Ant Colony Networks is introduced to solve the core fuel reload optimization problem.

  7. AntStar: Enhancing Optimization Problems by Integrating an Ant System and A⁎ Algorithm

    Directory of Open Access Journals (Sweden)

    Mohammed Faisal

    2016-01-01

    Full Text Available Recently, nature-inspired techniques have become valuable to many intelligent systems in different fields of technology and science. Among these techniques, Ant Systems (AS have become a valuable technique for intelligent systems in different fields. AS is a computational system inspired by the foraging behavior of ants and intended to solve practical optimization problems. In this paper, we introduce the AntStar algorithm, which is swarm intelligence based. AntStar enhances the optimization and performance of an AS by integrating the AS and A⁎ algorithm. Applying the AntStar algorithm to the single-source shortest-path problem has been done to ensure the efficiency of the proposed AntStar algorithm. The experimental result of the proposed algorithm illustrated the robustness and accuracy of the AntStar algorithm.

  8. Colony fusion and worker reproduction after queen loss in army ants

    DEFF Research Database (Denmark)

    Kronauer, Daniel J C; Schöning, Caspar; d'Ettorre, Patrizia

    2010-01-01

    Theory predicts that altruism is only evolutionarily stable if it is preferentially directed towards relatives, so that any such behaviour towards seemingly unrelated individuals requires scrutiny. Queenless army ant colonies, which have anecdotally been reported to fuse with queenright foreign...... colonies, are such an enigmatic case. Here we combine experimental queen removal with population genetics and cuticular chemistry analyses to show that colonies of the African army ant Dorylus molestus frequently merge with neighbouring colonies after queen loss. Merging colonies often have no direct co...

  9. Queen-worker caste ratio depends on colony size in the pharaoh ant (Monomorium pharaonis)

    DEFF Research Database (Denmark)

    Schmidt, Anna Mosegaard; Linksvayer, Timothy Arnold; Boomsma, Jacobus Jan

    2011-01-01

    affecting this variable remain scarcely studied. Maintaining polygynous pharaoh ant (Monomorium pharaonis) colonies in the laboratory has provided us with the opportunity to experimentally manipulate colony size, one of the key factors that can be expected to affect colony level queen–worker caste ratios......The success of an ant colony depends on the simultaneous presence of reproducing queens and nonreproducing workers in a ratio that will maximize colony growth and reproduction. Despite its presumably crucial role, queen–worker caste ratios (the ratio of adult queens to workers) and the factors...

  10. A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem

    Directory of Open Access Journals (Sweden)

    You Li

    2017-01-01

    Full Text Available The weapon-target assignment (WTA problem, known as an NP-complete problem, aims at seeking a proper assignment of weapons to targets. The biobjective WTA (BOWTA optimization model which maximizes the expected damage of the enemy and minimizes the cost of missiles is designed in this paper. A modified Pareto ant colony optimization (MPACO algorithm is used to solve the BOWTA problem. In order to avoid defects in traditional optimization algorithms and obtain a set of Pareto solutions efficiently, MPACO algorithm based on new designed operators is proposed, including a dynamic heuristic information calculation approach, an improved movement probability rule, a dynamic evaporation rate strategy, a global updating rule of pheromone, and a boundary symmetric mutation strategy. In order to simulate real air combat, the pilot operation factor is introduced into the BOWTA model. Finally, we apply the MPACO algorithm and other algorithms to the model and compare the data. Simulation results show that the proposed algorithm is successfully applied in the field of WTA which improves the performance of the traditional P-ACO algorithm effectively and produces better solutions than the two well-known multiobjective optimization algorithms NSGA-II and SPEA-II.

  11. Intraspecific Variation among Social Insect Colonies: Persistent Regional and Colony-Level Differences in Fire Ant Foraging Behavior.

    Directory of Open Access Journals (Sweden)

    Alison A Bockoven

    Full Text Available Individuals vary within a species in many ecologically important ways, but the causes and consequences of such variation are often poorly understood. Foraging behavior is among the most profitable and risky activities in which organisms engage and is expected to be under strong selection. Among social insects there is evidence that within-colony variation in traits such as foraging behavior can increase colony fitness, but variation between colonies and the potential consequences of such variation are poorly documented. In this study, we tested natural populations of the red imported fire ant, Solenopsis invicta, for the existence of colony and regional variation in foraging behavior and tested the persistence of this variation over time and across foraging habitats. We also reared single-lineage colonies in standardized environments to explore the contribution of colony lineage. Fire ants from natural populations exhibited significant and persistent colony and regional-level variation in foraging behaviors such as extra-nest activity, exploration, and discovery of and recruitment to resources. Moreover, colony-level variation in extra-nest activity was significantly correlated with colony growth, suggesting that this variation has fitness consequences. Lineage of the colony had a significant effect on extra-nest activity and exploratory activity and explained approximately half of the variation observed in foraging behaviors, suggesting a heritable component to colony-level variation in behavior.

  12. An ant colony optimization heuristic for an integrated production and distribution scheduling problem

    Science.gov (United States)

    Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju

    2014-04-01

    Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.

  13. Ant colony optimization and neural networks applied to nuclear power plant monitoring

    International Nuclear Information System (INIS)

    Santos, Gean Ribeiro dos; Andrade, Delvonei Alves de; Pereira, Iraci Martinez

    2015-01-01

    A recurring challenge in production processes is the development of monitoring and diagnosis systems. Those systems help on detecting unexpected changes and interruptions, preventing losses and mitigating risks. Artificial Neural Networks (ANNs) have been extensively used in creating monitoring systems. Usually the ANNs created to solve this kind of problem are created by taking into account only parameters as the number of inputs, outputs, and hidden layers. The result networks are generally fully connected and have no improvements in its topology. This work intends to use an Ant Colony Optimization (ACO) algorithm to create a tuned neural network. The ACO search algorithm will use Back Error Propagation (BP) to optimize the network topology by suggesting the best neuron connections. The result ANN will be applied to monitoring the IEA-R1 research reactor at IPEN. (author)

  14. Ant colony optimization-based firewall anomaly mitigation engine.

    Science.gov (United States)

    Penmatsa, Ravi Kiran Varma; Vatsavayi, Valli Kumari; Samayamantula, Srinivas Kumar

    2016-01-01

    A firewall is the most essential component of network perimeter security. Due to human error and the involvement of multiple administrators in configuring firewall rules, there exist common anomalies in firewall rulesets such as Shadowing, Generalization, Correlation, and Redundancy. There is a need for research on efficient ways of resolving such anomalies. The challenge is also to see that the reordered or resolved ruleset conforms to the organization's framed security policy. This study proposes an ant colony optimization (ACO)-based anomaly resolution and reordering of firewall rules called ACO-based firewall anomaly mitigation engine. Modified strategies are also introduced to automatically detect these anomalies and to minimize manual intervention of the administrator. Furthermore, an adaptive reordering strategy is proposed to aid faster reordering when a new rule is appended. The proposed approach was tested with different firewall policy sets. The results were found to be promising in terms of the number of conflicts resolved, with minimal availability loss and marginal security risk. This work demonstrated the application of a metaheuristic search technique, ACO, in improving the performance of a packet-filter firewall with respect to mitigating anomalies in the rules, and at the same time demonstrated conformance to the security policy.

  15. Enhanced ant colony optimization for inventory routing problem

    Science.gov (United States)

    Wong, Lily; Moin, Noor Hasnah

    2015-10-01

    The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

  16. Specialization and group size: brain and behavioural correlates of colony size in ants lacking morphological castes.

    Science.gov (United States)

    Amador-Vargas, Sabrina; Gronenberg, Wulfila; Wcislo, William T; Mueller, Ulrich

    2015-02-22

    Group size in both multicellular organisms and animal societies can correlate with the degree of division of labour. For ants, the task specialization hypothesis (TSH) proposes that increased behavioural specialization enabled by larger group size corresponds to anatomical specialization of worker brains. Alternatively, the social brain hypothesis proposes that increased levels of social stimuli in larger colonies lead to enlarged brain regions in all workers, regardless of their task specialization. We tested these hypotheses in acacia ants (Pseudomyrmex spinicola), which exhibit behavioural but not morphological task specialization. In wild colonies, we marked, followed and tested ant workers involved in foraging tasks on the leaves (leaf-ants) and in defensive tasks on the host tree trunk (trunk-ants). Task specialization increased with colony size, especially in defensive tasks. The relationship between colony size and brain region volume was task-dependent, supporting the TSH. Specifically, as colony size increased, the relative size of regions within the mushroom bodies of the brain decreased in trunk-ants but increased in leaf-ants; those regions play important roles in learning and memory. Our findings suggest that workers specialized in defence may have reduced learning abilities relative to leaf-ants; these inferences remain to be tested. In societies with monomorphic workers, brain polymorphism enhanced by group size could be a mechanism by which division of labour is achieved. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  17. A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

    OpenAIRE

    Lin Zhang; Na Yin; Xiong Fu; Qiaomin Lin; Ruchuan Wang

    2017-01-01

    With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems....

  18. A New Constructive Method for Electric Power System Reconfiguration Using Ant Colony

    Directory of Open Access Journals (Sweden)

    Habib HAMDAOUI

    2008-06-01

    Full Text Available This electric power distribution system delivers power to the customers from a set of distribution substations. While the transmission lines are configured in a meshed network, the distribution feeders are configured radially in almost all cases. The proposed problem in this work is to determine the optimal topology among a various alternatives. This problem is known as a problem of total investment-cost minimization, subject to power constraints. In fact, the paper addresses an ant colony met-heuristic optimization method to solve this combinatorial problem. Due to the variation of demand, the reconfiguration may be considered in two different situations: in the system planning or system design stage. The proposed met-heuristic determines the minimal investment-cost system configuration during the considered study period to satisfy power transit constraints. The algorithm of ant colony approach (ACA is required to identify the optimal combination of adding or cut off feeders with different parameters for the new topology design.

  19. Targeted Removal of Ant Colonies in Ecological Experiments, Using Hot Water

    OpenAIRE

    Tschinkel, Walter R.; King, Joshua R.

    2007-01-01

    Ecological experiments on fire ants cannot, or should not, use poison baits to eliminate the fire ants because such baits are not specific to fire ants, or even to ants. Hot water is an extremely effective and specific killing agent for fire ant colonies, but producing large amounts of hot water in the field, and making the production apparatus mobile have been problematical. The construction and use of a charcoal-fired kiln made from a 55-gal. oil drum lined with a sand-fireclay mixture is d...

  20. Temnothorax rugatulus ant colonies consistently vary in nest structure across time and context.

    Directory of Open Access Journals (Sweden)

    Nicholas DiRienzo

    Full Text Available A host of animals build architectural constructions. Such constructions frequently vary with environmental and individual/colony conditions, and their architecture directly influences behavior and fitness. The nests of ant colonies drive and enable many of their collective behaviors, and as such are part of their 'extended phenotype'. Since ant colonies have been recently shown to differ in behavior and life history strategy, we ask whether colonies differ in another trait: the architecture of the constructions they create. We allowed Temnothorax rugatulus rock ants, who create nests by building walls within narrow rock gaps, to repeatedly build nest walls in a fixed crevice but under two environmental conditions. We find that colonies consistently differ in their architecture across environments and over nest building events. Colony identity explained 12-40% of the variation in nest architecture, while colony properties and environmental conditions explained 5-20%, as indicated by the condition and marginal R2 values. When their nest boxes were covered, which produced higher humidity and lower airflow, colonies built thicker, longer, and heavier walls. Colonies also built more robust walls when they had more brood, suggesting a protective function of wall thickness. This is, to our knowledge, the first study to explicitly investigate the repeatability of nestbuilding behavior in a controlled environment. Our results suggest that colonies may face tradeoffs, perhaps between factors such as active vs. passive nest defense, and that selection may act on individual construction rules as a mechanisms to mediate colony-level behavior.

  1. Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

    International Nuclear Information System (INIS)

    Hou, Huirang; Zheng, Dandan; Nie, Laixiao

    2015-01-01

    For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until –10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method. (paper)

  2. Ant colony optimisation for economic dispatch problem with non-smooth cost functions

    Energy Technology Data Exchange (ETDEWEB)

    Pothiya, Saravuth; Kongprawechnon, Waree [School of Communication, Instrumentation and Control, Sirindhorn International Institute of Technology, Thammasat University, P.O. Box 22, Pathumthani (Thailand); Ngamroo, Issarachai [Center of Excellence for Innovative Energy Systems, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Bangkok 10520 (Thailand)

    2010-06-15

    This paper presents a novel and efficient optimisation approach based on the ant colony optimisation (ACO) for solving the economic dispatch (ED) problem with non-smooth cost functions. In order to improve the performance of ACO algorithm, three additional techniques, i.e. priority list, variable reduction, and zoom feature are presented. To show its efficiency and effectiveness, the proposed ACO is applied to two types of ED problems with non-smooth cost functions. Firstly, the ED problem with valve-point loading effects consists of 13 and 40 generating units. Secondly, the ED problem considering the multiple fuels consists of 10 units. Additionally, the results of the proposed ACO are compared with those of the conventional heuristic approaches. The experimental results show that the proposed ACO approach is comparatively capable of obtaining higher quality solution and faster computational time. (author)

  3. The Lobe Fissure Tracking by the Modified Ant Colony Optimization Framework in CT Images

    Directory of Open Access Journals (Sweden)

    Chii-Jen Chen

    2014-11-01

    Full Text Available Chest computed tomography (CT is the most commonly used technique for the inspection of lung lesions. However, the lobe fissures in lung CT is still difficult to observe owing to its imaging structure. Therefore, in this paper, we aimed to develop an efficient tracking framework to extract the lobe fissures by the proposed modified ant colony optimization (ACO algorithm. We used the method of increasing the consistency of pheromone on lobe fissure to improve the accuracy of path tracking. In order to validate the proposed system, we had tested our method in a database from 15 lung patients. In the experiment, the quantitative assessment shows that the proposed ACO method achieved the average F-measures of 80.9% and 82.84% in left and right lungs, respectively. The experiments indicate our method results more satisfied performance, and can help investigators detect lung lesion for further examination.

  4. Pupae transplantation to boost early colony growth in the weaver ant Oecophylla longinoda Latreille (Hymenoptera: Formicidae)

    DEFF Research Database (Denmark)

    Ouagoussounon, Issa; Sinzogan, Antonio; Offenberg, Joachim

    2013-01-01

    Oecophylla ants are currently used for biological control in fruit plantations in Australia, Asia and Africa and for protein production in Asia. To further improve the technology and implement it on a large scale, effective and fast production of live colonies is desirable. Early colony developme...

  5. Collective Intelligence for Optimal Power Flow Solution Using Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Boumediène ALLAOUA

    2008-12-01

    Full Text Available This paper presents the performance ant collective intelligence efficiency for electrical network. Solutions for Optimal Power Flow (OPF problem of a power system deliberate via an ant colony optimization metaheuristic method. The objective is to minimize the total fuel cost of thermal generating units and also conserve an acceptable system performance in terms of limits on generator real and reactive power outputs, bus voltages, shunt capacitors/reactors, transformers tap-setting and power flow of transmission lines. Simulation results on the IEEE 30-bus electrical network show that the ant colony optimization method converges quickly to the global optimum.

  6. Balancing emergency message dissemination and network lifetime in wireless body area network using ant colony optimization and Bayesian game formulation

    Directory of Open Access Journals (Sweden)

    R. Latha

    Full Text Available Nowadays, Wireless Body Area Network (WBAN is emerging very fast and so many new methods and algorithms are coming up for finding the optimal path for disseminating emergency messages. Ant Colony Optimization (ACO is one of the cultural algorithms for solving many hard problems such as Travelling Salesman Problem (TSP. ACO is a natural behaviour of ants, which work stochastically with the help of pheromone trails deposited in the shortest route to find their food. This optimization procedure involves adapting, positive feedback and inherent parallelism. Each ant will deposit certain amount of pheromone in the tour construction it makes searching for food. This type of communication is known as stigmetric communication. In addition, if a dense WBAN environment prevails, such as hospital, i.e. in the environment of overlapping WBAN, game formulation was introduced for analyzing the mixed strategy behaviour of WBAN. In this paper, the ant colony optimization approach to the travelling salesman problem was applied to the WBAN to determine the shortest route for sending emergency message to the doctor via sensor nodes; and also a static Bayesian game formulation with mixed strategy was analysed to enhance the network lifetime. Whenever the patient needs any critical care or any other medical issue arises, emergency messages will be created by the WBAN and sent to the doctor's destination. All the modes of communication were realized in a simulation environment using OMNet++. The authors investigated a balanced model of emergency message dissemination and network lifetime in WBAN using ACO and Bayesian game formulation. Keywords: Wireless body area network, Ant colony optimization, Bayesian game model, Sensor network, Message latency, Network lifetime

  7. Extreme queen-mating frequency and colony fission in African army ants

    DEFF Research Database (Denmark)

    Kronauer, Daniel J C; Schoning, Caspar; Pedersen, Jes S

    2004-01-01

    Army ants have long been suspected to represent an independent origin of multiple queen-mating in the social Hymenoptera. Using microsatellite markers, we show that queens of the African army ant Dorylus (Anomma) molestus have the highest absolute (17.3) and effective (17.5) queen......-mating frequencies reported so far for ants. This confirms that obligate multiple queen-mating in social insects is associated with large colony size and advanced social organization, but also raises several novel questions. First, these high estimates place army ants in the range of mating frequencies of honeybees......, which have so far been regarded as odd exceptions within the social Hymenoptera. Army ants and honeybees are fundamentally different in morphology and life history, but are the only social insects known that combine obligate multiple mating with reproduction by colony fission and extremely male...

  8. The Role of Non-Foraging Nests in Polydomous Wood Ant Colonies.

    Science.gov (United States)

    Ellis, Samuel; Robinson, Elva J H

    2015-01-01

    A colony of red wood ants can inhabit more than one spatially separated nest, in a strategy called polydomy. Some nests within these polydomous colonies have no foraging trails to aphid colonies in the canopy. In this study we identify and investigate the possible roles of non-foraging nests in polydomous colonies of the wood ant Formica lugubris. To investigate the role of non-foraging nests we: (i) monitored colonies for three years; (ii) observed the resources being transported between non-foraging nests and the rest of the colony; (iii) measured the amount of extra-nest activity around non-foraging and foraging nests. We used these datasets to investigate the extent to which non-foraging nests within polydomous colonies are acting as: part of the colony expansion process; hunting and scavenging specialists; brood-development specialists; seasonal foragers; or a selfish strategy exploiting the foraging effort of the rest of the colony. We found that, rather than having a specialised role, non-foraging nests are part of the process of colony expansion. Polydomous colonies expand by founding new nests in the area surrounding the existing nests. Nests founded near food begin foraging and become part of the colony; other nests are not founded near food sources and do not initially forage. Some of these non-foraging nests eventually begin foraging; others do not and are abandoned. This is a method of colony growth not available to colonies inhabiting a single nest, and may be an important advantage of the polydomous nesting strategy, allowing the colony to expand into profitable areas.

  9. Multiobjective Evolution of Biped Robot Gaits Using Advanced Continuous Ant-Colony Optimized Recurrent Neural Networks.

    Science.gov (United States)

    Juang, Chia-Feng; Yeh, Yen-Ting

    2017-06-30

    This paper proposes the optimization of a fully connected recurrent neural network (FCRNN) using advanced multiobjective continuous ant colony optimization (AMO-CACO) for the multiobjective gait generation of a biped robot (the NAO). The FCRNN functions as a central pattern generator and is optimized to generate angles of the hip roll and pitch, the knee pitch, and the ankle pitch and roll. The performance of the FCRNN-generated gait is evaluated according to the walking speed, trajectory straightness, oscillations of the body in the pitch and yaw directions, and walking posture, subject to the basic constraints that the robot cannot fall down and must walk forward. This paper formulates this gait generation task as a constrained multiobjective optimization problem and solves this problem through an AMO-CACO-based evolutionary learning approach. The AMO-CACO finds Pareto optimal solutions through ant-path selection and sampling operations by introducing an accumulated rank for the solutions in each single-objective function into solution sorting to improve learning performance. Simulations are conducted to verify the AMO-CACO-based FCRNN gait generation performance through comparisons with different multiobjective optimization algorithms. Selected software-designed Pareto optimal FCRNNs are then applied to control the gait of a real NAO robot.

  10. The scent of supercolonies: the discovery, synthesis and behavioural verification of ant colony recognition cues

    Directory of Open Access Journals (Sweden)

    Sulc Robert

    2009-10-01

    Full Text Available Abstract Background Ants form highly social and cooperative colonies that compete, and often fight, against other such colonies, both intra- and interspecifically. Some invasive ants take sociality to an extreme, forming geographically massive 'supercolonies' across thousands of kilometres. The success of social insects generally, as well as invasive ants in particular, stems from the sophisticated mechanisms used to accurately and precisely distinguish colonymates from non-colonymates. Surprisingly, however, the specific chemicals used for this recognition are virtually undescribed. Results Here, we report the discovery, chemical synthesis and behavioural testing of the colonymate recognition cues used by the widespread and invasive Argentine ant (Linepithema humile. By synthesizing pure versions of these chemicals in the laboratory and testing them in behavioural assays, we show that these compounds trigger aggression among normally amicable nestmates, but control hydrocarbons do not. Furthermore, behavioural testing across multiple different supercolonies reveals that the reaction to individual compounds varies from colony to colony -- the expected reaction to true colony recognition labels. Our results also show that both quantitative and qualitative changes to cuticular hydrocarbon profiles can trigger aggression among nestmates. These data point the way for the development of new environmentally-friendly control strategies based on the species-specific manipulation of aggressive behaviour. Conclusion Overall, our findings reveal the identity of specific chemicals used for colonymate recognition by the invasive Argentine ants. Although the particular chemicals used by other ants may differ, the patterns reported here are likely to be true for ants generally. As almost all invasive ants display widespread unicoloniality in their introduced ranges, our findings are particularly relevant for our understanding of the biology of these damaging

  11. Blochmannia endosymbionts improve colony growth and immune defence in the ant Camponotus fellah

    Directory of Open Access Journals (Sweden)

    Depoix Delphine

    2009-02-01

    Full Text Available Abstract Background Microorganisms are a large and diverse form of life. Many of them live in association with large multicellular organisms, developing symbiotic relations with the host and some have even evolved to form obligate endosymbiosis 1. All Carpenter ants (genus Camponotus studied hitherto harbour primary endosymbiotic bacteria of the Blochmannia genus. The role of these bacteria in ant nutrition has been demonstrated 2 but the omnivorous diet of these ants lead us to hypothesize that the bacteria might provide additional advantages to their host. In this study, we establish links between Blochmannia, growth of starting new colonies and the host immune response. Results We manipulated the number of bacterial endosymbionts in incipient laboratory-reared colonies of Camponotus fellah by administrating doses of an antibiotic (Rifampin mixed in honey-solution. Efficiency of the treatment was estimated by quantitative polymerase chain reaction and Fluorescent in situ hybridization (FISH, using Blochmannia specific primers (qPCR and two fluorescent probes (one for all Eubacterial and other specific for Blochmannia. Very few or no bacteria could be detected in treated ants. Incipient Rifampin treated colonies had significantly lower numbers of brood and adult workers than control colonies. The immune response of ants from control and treated colonies was estimated by inserting nylon filaments in the gaster and removing it after 24 h. In the control colonies, the encapsulation response was positively correlated to the bacterial amount, while no correlation was observed in treated colonies. Indeed, antibiotic treatment increased the encapsulation response of the workers, probably due to stress conditions. Conclusion The increased growth rate observed in non-treated colonies confirms the importance of Blochmannia in this phase of colony development. This would provide an important selective advantage during colony founding, where the colonies

  12. Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2014-01-01

    Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.

  13. Dose response of red imported fire ant colonies to Solenopsis invicta virus 3.

    Science.gov (United States)

    Valles, Steven M; Porter, Sanford D

    2015-10-01

    Baiting tests were conducted to evaluate the effect of increasing Solenopsis invicta virus 3 (SINV-3) dose on fire ant colonies. Actively growing early-stage fire ant (Solenopsis invicta Buren) laboratory colonies were pulse-exposed for 24 hours to six concentrations of SINV-3 (10(1), 10(3), 10(5), 10(7), 10(9) genome equivalents/μl) in 1 ml of a 10 % sucrose bait and monitored regularly for two months. SINV-3 concentration had a significant effect on colony health. Brood rating (proportion of brood to worker ants) began to depart from the control group at 19 days for the 10(9) concentration and 26 days for the 10(7) concentration. At 60 days, brood rating was significantly lower among colonies treated with 10(9), 10(7), and 10(5) SINV-3 concentrations. The intermediate concentration, 10(5), appeared to cause a chronic, low-level infection with one colony (n = 9) supporting virus replication. Newly synthesized virus was not detected in any fire ant colonies treated at the 10(1) concentration, indicating that active infections failed to be established at this level of exposure. The highest bait concentration chosen, 10(9), appeared most effective from a control aspect; mean colony brood rating at this concentration (1.1 ± 0.9 at the 60 day time point) indicated poor colony health with minimal brood production. No clear relationship was observed between the quantity of plus genome strand detected and brood rating. Conversely, there was a strong relationship between the presence of the replicative genome strand and declining brood rating, which may serve as a predictor of disease severity. Recommendations for field treatment levels to control fire ants with SINV-3 are discussed.

  14. A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks.

    Science.gov (United States)

    Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

    2017-03-08

    With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes' reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes' communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.

  15. A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Lin Zhang

    2017-03-01

    Full Text Available With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR. This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.

  16. Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization.

    Science.gov (United States)

    Juang, Chia-Feng; Hsu, Chia-Hung

    2009-12-01

    This paper proposes a new reinforcement-learning method using online rule generation and Q-value-aided ant colony optimization (ORGQACO) for fuzzy controller design. The fuzzy controller is based on an interval type-2 fuzzy system (IT2FS). The antecedent part in the designed IT2FS uses interval type-2 fuzzy sets to improve controller robustness to noise. There are initially no fuzzy rules in the IT2FS. The ORGQACO concurrently designs both the structure and parameters of an IT2FS. We propose an online interval type-2 rule generation method for the evolution of system structure and flexible partitioning of the input space. Consequent part parameters in an IT2FS are designed using Q -values and the reinforcement local-global ant colony optimization algorithm. This algorithm selects the consequent part from a set of candidate actions according to ant pheromone trails and Q-values, both of which are updated using reinforcement signals. The ORGQACO design method is applied to the following three control problems: 1) truck-backing control; 2) magnetic-levitation control; and 3) chaotic-system control. The ORGQACO is compared with other reinforcement-learning methods to verify its efficiency and effectiveness. Comparisons with type-1 fuzzy systems verify the noise robustness property of using an IT2FS.

  17. The relationship between canopy cover and colony size of the wood ant Formica lugubris--implications for the thermal effects on a keystone ant species.

    Directory of Open Access Journals (Sweden)

    Yi-Huei Chen

    Full Text Available Climate change may affect ecosystems and biodiversity through the impacts of rising temperature on species' body size. In terms of physiology and genetics, the colony is the unit of selection for ants so colony size can be considered the body size of a colony. For polydomous ant species, a colony is spread across several nests. This study aims to clarify how climate change may influence an ecologically significant ant species group by investigating thermal effects on wood ant colony size. The strong link between canopy cover and the local temperatures of wood ant's nesting location provides a feasible approach for our study. Our results showed that nests were larger in shadier areas where the thermal environment was colder and more stable compared to open areas. Colonies (sum of nests in a polydomous colony also tended to be larger in shadier areas than in open areas. In addition to temperature, our results supported that food resource availability may be an additional factor mediating the relationship between canopy cover and nest size. The effects of canopy cover on total colony size may act at the nest level because of the positive relationship between total colony size and mean nest size, rather than at the colony level due to lack of link between canopy cover and number of nests per colony. Causal relationships between the environment and the life-history characteristics may suggest possible future impacts of climate change on these species.

  18. The relationship between canopy cover and colony size of the wood ant Formica lugubris--implications for the thermal effects on a keystone ant species.

    Science.gov (United States)

    Chen, Yi-Huei; Robinson, Elva J H

    2014-01-01

    Climate change may affect ecosystems and biodiversity through the impacts of rising temperature on species' body size. In terms of physiology and genetics, the colony is the unit of selection for ants so colony size can be considered the body size of a colony. For polydomous ant species, a colony is spread across several nests. This study aims to clarify how climate change may influence an ecologically significant ant species group by investigating thermal effects on wood ant colony size. The strong link between canopy cover and the local temperatures of wood ant's nesting location provides a feasible approach for our study. Our results showed that nests were larger in shadier areas where the thermal environment was colder and more stable compared to open areas. Colonies (sum of nests in a polydomous colony) also tended to be larger in shadier areas than in open areas. In addition to temperature, our results supported that food resource availability may be an additional factor mediating the relationship between canopy cover and nest size. The effects of canopy cover on total colony size may act at the nest level because of the positive relationship between total colony size and mean nest size, rather than at the colony level due to lack of link between canopy cover and number of nests per colony. Causal relationships between the environment and the life-history characteristics may suggest possible future impacts of climate change on these species.

  19. Mechanisms of social regulation change across colony development in an ant.

    Science.gov (United States)

    Moore, Dani; Liebig, Jürgen

    2010-10-27

    Mutual policing is an important mechanism for reducing conflict in cooperative groups. In societies of ants, bees, and wasps, mutual policing of worker reproduction can evolve when workers are more closely related to the queen's sons than to the sons of workers or when the costs of worker reproduction lower the inclusive fitness of workers. During colony growth, relatedness within the colony remains the same, but the costs of worker reproduction may change. The costs of worker reproduction are predicted to be greatest in incipient colonies. If the costs associated with worker reproduction outweigh the individual direct benefits to workers, policing mechanisms as found in larger colonies may be absent in incipient colonies. We investigated policing behaviour across colony growth in the ant Camponotus floridanus. In large colonies of this species, worker reproduction is policed by the destruction of worker-laid eggs. We found workers from incipient colonies do not exhibit policing behaviour, and instead tolerate all conspecific eggs. The change in policing behaviour is consistent with changes in egg surface hydrocarbons, which provide the informational basis for policing; eggs laid by queens from incipient colonies lack the characteristic hydrocarbons on the surface of eggs laid by queens from large colonies, making them chemically indistinguishable from worker-laid eggs. We also tested the response to fertility information in the context of queen tolerance. Workers from incipient colonies attacked foreign queens from large colonies; whereas workers from large colonies tolerated such queens. Workers from both incipient and large colonies attacked foreign queens from incipient colonies. Our results provide novel insights into the regulation of worker reproduction in social insects at both the proximate and ultimate levels. At the proximate level, our results show that mechanisms of social regulation, such as the response to fertility signals, change dramatically over

  20. Mechanisms of social regulation change across colony development in an ant

    Directory of Open Access Journals (Sweden)

    Liebig Jürgen

    2010-10-01

    Full Text Available Abstract Background Mutual policing is an important mechanism for reducing conflict in cooperative groups. In societies of ants, bees, and wasps, mutual policing of worker reproduction can evolve when workers are more closely related to the queen's sons than to the sons of workers or when the costs of worker reproduction lower the inclusive fitness of workers. During colony growth, relatedness within the colony remains the same, but the costs of worker reproduction may change. The costs of worker reproduction are predicted to be greatest in incipient colonies. If the costs associated with worker reproduction outweigh the individual direct benefits to workers, policing mechanisms as found in larger colonies may be absent in incipient colonies. Results We investigated policing behaviour across colony growth in the ant Camponotus floridanus. In large colonies of this species, worker reproduction is policed by the destruction of worker-laid eggs. We found workers from incipient colonies do not exhibit policing behaviour, and instead tolerate all conspecific eggs. The change in policing behaviour is consistent with changes in egg surface hydrocarbons, which provide the informational basis for policing; eggs laid by queens from incipient colonies lack the characteristic hydrocarbons on the surface of eggs laid by queens from large colonies, making them chemically indistinguishable from worker-laid eggs. We also tested the response to fertility information in the context of queen tolerance. Workers from incipient colonies attacked foreign queens from large colonies; whereas workers from large colonies tolerated such queens. Workers from both incipient and large colonies attacked foreign queens from incipient colonies. Conclusions Our results provide novel insights into the regulation of worker reproduction in social insects at both the proximate and ultimate levels. At the proximate level, our results show that mechanisms of social regulation, such as

  1. An ant colony based resilience approach to cascading failures in cluster supply network

    Science.gov (United States)

    Wang, Yingcong; Xiao, Renbin

    2016-11-01

    Cluster supply chain network is a typical complex network and easily suffers cascading failures under disruption events, which is caused by the under-load of enterprises. Improving network resilience can increase the ability of recovery from cascading failures. Social resilience is found in ant colony and comes from ant's spatial fidelity zones (SFZ). Starting from the under-load failures, this paper proposes a resilience method to cascading failures in cluster supply chain network by leveraging on social resilience of ant colony. First, the mapping between ant colony SFZ and cluster supply chain network SFZ is presented. Second, a new cascading model for cluster supply chain network is constructed based on under-load failures. Then, the SFZ-based resilience method and index to cascading failures are developed according to ant colony's social resilience. Finally, a numerical simulation and a case study are used to verify the validity of the cascading model and the resilience method. Experimental results show that, the cluster supply chain network becomes resilient to cascading failures under the SFZ-based resilience method, and the cluster supply chain network resilience can be enhanced by improving the ability of enterprises to recover and adjust.

  2. Host specificity and colony impacts of the fire ant pathogen, Solenopsis invicta virus 3.

    Science.gov (United States)

    Porter, Sanford D; Valles, Steven M; Oi, David H

    2013-09-01

    An understanding of host specificity is essential before pathogens can be used as biopesticides or self-sustaining biocontrol agents. In order to define the host range of the recently discovered Solenopsis invicta virus 3 (SINV-3), we exposed laboratory colonies of 19 species of ants in 14 genera and 4 subfamilies to this virus. Despite extreme exposure during these tests, active, replicating infections only occurred in Solenopsis invicta Buren and hybrid (S. invicta×S. richteri) fire ant colonies. The lack of infections in test Solenopsis geminata fire ants from the United States indicates that SINV-3 is restricted to the saevissima complex of South American fire ants, especially since replicating virus was also found in several field-collected samples of the black imported fire ant, Solenopsis richteri Forel. S. invicta colonies infected with SINV-3 declined dramatically with average brood reductions of 85% or more while colonies of other species exposed to virus remained uninfected and healthy. The combination of high virulence and high host specificity suggest that SINV-3 has the potential for use as either a biopesticide or a self-sustaining biocontrol agent. Published by Elsevier Inc.

  3. Blending of heritable recognition cues among ant nestmates creates distinct colony gestalt odours but prevents within-colony nepotism

    DEFF Research Database (Denmark)

    van Zweden, Jelle Stijn; Brask, Josefine B.; Christensen, Jan H.

    2010-01-01

    members to create a Gestalt odour. Although earlier studies have established that hydrocarbon profiles are influenced by heritable factors, transfer among nestmates and additional environmental factors, no studies have quantified these relative contributions for separate compounds. Here, we use the ant...... discrimination or as nestmate recognition cues. These results indicate that heritable compounds are suitable for establishing a genetic Gestalt for efficient nestmate recognition, but that recognition cues within colonies are insufficiently distinct to allow nepotistic kin discrimination....

  4. External immunity in ant societies: sociality and colony size do not predict investment in antimicrobials

    Science.gov (United States)

    Halawani, Omar; Pearson, Bria; Mathews, Stephanie; López-Uribe, Margarita M.; Dunn, Robert R.; Smith, Adrian A.

    2018-01-01

    Social insects live in dense groups with a high probability of disease transmission and have therefore faced strong pressures to develop defences against pathogens. For this reason, social insects have been hypothesized to invest in antimicrobial secretions as a mechanism of external immunity to prevent the spread of disease. However, empirical studies linking the evolution of sociality with increased investment in antimicrobials have been relatively few. Here we quantify the strength of antimicrobial secretions among 20 ant species that cover a broad spectrum of ant diversity and colony sizes. We extracted external compounds from ant workers to test whether they inhibited the growth of the bacterium Staphylococcus epidermidis. Because all ant species are highly social, we predicted that all species would exhibit some antimicrobial activity and that species that form the largest colonies would exhibit the strongest antimicrobial response. Our comparative approach revealed that strong surface antimicrobials are common to particular ant clades, but 40% of species exhibited no antimicrobial activity at all. We also found no correlation between antimicrobial activity and colony size. Rather than relying on antimicrobial secretions as external immunity to control pathogen spread, many ant species have probably developed alternative strategies to defend against disease pressure. PMID:29515850

  5. An ant colony optimization based feature selection for web page classification.

    Science.gov (United States)

    Saraç, Esra; Özel, Selma Ayşe

    2014-01-01

    The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

  6. Arboreal Ant Colonies as ‘Hot-Points’ of Cryptic Diversity for Myrmecophiles: The Weaver Ant Camponotus sp. aff. textor and Its Interaction Network with Its Associates

    OpenAIRE

    Pérez-Lachaud, Gabriela; Lachaud, Jean-Paul

    2014-01-01

    INTRODUCTION: Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biod...

  7. Aplicación de un algoritmo ACO al problema de taller de flujo de permutación con tiempos de preparación dependientes de la secuencia y minimización de makespan An ant colony algorithm for the permutation flowshop with sequence dependent setup times and makespan minimization

    Directory of Open Access Journals (Sweden)

    Eduardo Salazar Hornig

    2011-08-01

    Full Text Available En este trabajo se estudió el problema de secuenciamiento de trabajos en el taller de flujo de permutación con tiempos de preparación dependientes de la secuencia y minimización de makespan. Para ello se propuso un algoritmo de optimización mediante colonia de hormigas (ACO, llevando el problema original a una estructura semejante al problema del vendedor viajero TSP (Traveling Salesman Problem asimétrico, utilizado para su evaluación problemas propuestos en la literatura y se compara con una adaptación de la heurística NEH (Nawaz-Enscore-Ham. Posteriormente se aplica una búsqueda en vecindad a la solución obtenida tanto por ACO como NEH.This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic.

  8. Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

    Science.gov (United States)

    Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

    2018-04-01

    Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

  9. Social prophylaxis: group interaction promotes collective immunity in ant colonies

    DEFF Research Database (Denmark)

    Ugelvig, Line V; Cremer, Sylvia

    2007-01-01

    , infection of the brood was prevented in our experiment by behavioral changes of treated and naive workers. Parasite-treated ants stayed away from the brood chamber, whereas their naive nestmates increased brood-care activities. Our findings reveal a direct benefit for individuals to perform hygienic......Life in a social group increases the risk of disease transmission. To counteract this threat, social insects have evolved manifold antiparasite defenses, ranging from social exclusion of infected group members to intensive care. It is generally assumed that individuals performing hygienic behaviors...... risk infecting themselves, suggesting a high direct cost of helping. Our work instead indicates the opposite for garden ants. Social contact with individual workers, which were experimentally exposed to a fungal parasite, provided a clear survival benefit to nontreated, naive group members upon later...

  10. Influence of toxic bait type and starvation on worker and queen mortality in laboratory colonies of Argentine ant (Hymenoptera: Formicidae).

    Science.gov (United States)

    Mathieson, Melissa; Toft, Richard; Lester, Philip J

    2012-08-01

    The efficacy of toxic baits should be judged by their ability to kill entire ant colonies, including the colony queen or queens. We studied the efficacy of four toxic baits to the Argentine ant, Linepithema humile (Mayr) (Hymenoptera: Formicidae). These baits were Xstinguish that has the toxicant fipronil, Exterm-an-Ant that contains both boric acid and sodium borate, and Advion ant gel and Advion ant bait arena that both have indoxacarb. Experimental nests contained 300 workers and 10 queen ants that were starved for either 24 or 48 h before toxic bait exposure. The efficacy of the toxic baits was strongly influenced by starvation. In no treatment with 24-h starvation did we observe 100% worker death. After 24-h starvation three of the baits did not result in any queen deaths, with only Exterm-an-Ant producing an average of 25% mortality. In contrast, 100% queen and worker mortality was observed in colonies starved for 48 h and given Xstinguish or Exterm-an-Ant. The baits Advion ant gel and Advion ant bait arena were not effective against Argentine ants in these trials, resulting in ants are likely to be starved. Our results suggest queen mortality must be assessed in tests for toxic bait efficacy. Our data indicate that of these four baits, Xstinguish and Exterm-an-Ant are the best options for control of Argentine ants in New Zealand.

  11. Statistical Performance Analysis of an Ant-Colony Optimisation Application in S-Net

    NARCIS (Netherlands)

    MacKenzie, K.; Hölzenspies, P.K.F.; Hammond, K.; Kirner, R.; Nguyen, V.T.N.; te Boekhorst, R.; Grelck, C.; Poss, R.; Verstraaten, M.; Grelck, C.; Hammond, K.; Scholz, S.B.

    2013-01-01

    We consider an ant-colony optimsation problem implemented on a multicore system as a collection of asynchronous streamprocessing components under the control of the S-NET coordination language. Statistical analysis and visualisation techniques are used to study the behaviour of the application, and

  12. Sociogenomics of cooperation and conflict during colony foundation in the fire ant Solenopsis invicta

    Science.gov (United States)

    The genomic state of an individual results from the interplay between its internal condition and the external environment, which may include the social environment. The link between genes and social environment is clearly visible during the process of colony founding in the fire ant Solenopsis invic...

  13. Colony growth of two species of Solenopsis fire ants(Hymenoptera: Formicidae) reared with crickets and beef liver

    Science.gov (United States)

    Most diets for rearing fire ants and other ants contain insects such as crickets or mealworms. Unfortunately, insect diets are expensive, especially for large rearing operations, and are not always easily available. This study was designed to examine colony growth of Solenopsis fire ants on beef liv...

  14. A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jing Yang

    2010-05-01

    Full Text Available For monitoring burst events in a kind of reactive wireless sensor networks (WSNs, a multipath routing protocol (MRP based on dynamic clustering and ant colony optimization (ACO is proposed.. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

  15. A sequential fuzzy diagnosis method for rotating machinery using ant colony optimization and possibility theory

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Hao; Ping, Xueliang; Cao, Yi; Lie, Ke [Jiangnan University, Wuxi (China); Chen, Peng [Mie University, Mie (Japan); Wang, Huaqing [Beijing University, Beijing (China)

    2014-04-15

    This study proposes a novel intelligent fault diagnosis method for rotating machinery using ant colony optimization (ACO) and possibility theory. The non-dimensional symptom parameters (NSPs) in the frequency domain are defined to reflect the features of the vibration signals measured in each state. A sensitive evaluation method for selecting good symptom parameters using principal component analysis (PCA) is proposed for detecting and distinguishing faults in rotating machinery. By using ACO clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. A fuzzy diagnosis method using sequential inference and possibility theory is also proposed, by which the conditions of the machinery can be identified sequentially. Lastly, the proposed method is compared with a conventional neural networks (NN) method. Practical examples of diagnosis for a V-belt driving equipment used in a centrifugal fan are provided to verify the effectiveness of the proposed method. The results verify that the faults that often occur in V-belt driving equipment, such as a pulley defect state, a belt defect state and a belt looseness state, are effectively identified by the proposed method, while these faults are difficult to detect using conventional NN.

  16. Utilisation of multiple queens and pupae transplantation to boost early colony growth of weaver ants Oecophylla smaragdina

    DEFF Research Database (Denmark)

    Peng, Renkang; Nielsen, Mogens Gissel; Offenberg, Joachim

    2013-01-01

    Weaver ants (Oecophylla smaragdina Fabricius) have been increasingly used as biocontrol agents of insect pests and as insect protein for human food and animals. For either of these purposes, mature ant colonies are essential. However, for a newly established colony to develop to a suitable mature...... donor colony was conducted in 2010 at Darwin, Australia. The survival rates of the imago workers from transplanted pupae ranged between 73 - 97%, suggesting that queens in incipient colonies accepted foreign pupae. Colony size was positively related to the number of founding queens. Compared...

  17. Variation in Butterfly Larval Acoustics as a Strategy to Infiltrate and Exploit Host Ant Colony Resources

    Science.gov (United States)

    Sala, Marco; Casacci, Luca Pietro; Balletto, Emilio; Bonelli, Simona; Barbero, Francesca

    2014-01-01

    About 10,000 arthropods live as ants' social parasites and have evolved a number of mechanisms allowing them to penetrate and survive inside the ant nests. Many of them can intercept and manipulate their host communication systems. This is particularly important for butterflies of the genus Maculinea, which spend the majority of their lifecycle inside Myrmica ant nests. Once in the colony, caterpillars of Maculinea “predatory species” directly feed on the ant larvae, while those of “cuckoo species” are fed primarily by attendance workers, by trophallaxis. It has been shown that Maculinea cuckoo larvae are able to reach a higher social status within the colony's hierarchy by mimicking the acoustic signals of their host queen ants. In this research we tested if, when and how myrmecophilous butterflies may change sound emissions depending on their integration level and on stages of their life cycle. We studied how a Maculinea predatory species (M. teleius) can acoustically interact with their host ants and highlighted differences with respect to a cuckoo species (M. alcon). We recorded sounds emitted by Maculinea larvae as well as by their Myrmica hosts, and performed playback experiments to assess the parasites' capacity to interfere with the host acoustic communication system. We found that, although varying between and within butterfly species, the larval acoustic emissions are more similar to queens' than to workers' stridulations. Nevertheless playback experiments showed that ant workers responded most strongly to the sounds emitted by the integrated (i.e. post-adoption) larvae of the cuckoo species, as well as by those of predatory species recorded before any contact with the host ants (i.e. in pre-adoption), thereby revealing the role of acoustic signals both in parasite integration and in adoption rituals. We discuss our findings in the broader context of parasite adaptations, comparing effects of acoustical and chemical mimicry. PMID:24718496

  18. The application of ant colony optimization in the solution of 3D traveling salesman problem on a sphere

    Directory of Open Access Journals (Sweden)

    Hüseyin Eldem

    2017-08-01

    Full Text Available Traveling Salesman Problem (TSP is a problem in combinatorial optimization that should be solved by a salesperson who has to travel all cities at the minimum cost (minimum route and return to the starting city (node. Todays, to resolve the minimum cost of this problem, many optimization algorithms have been used. The major ones are these metaheuristic algorithms. In this study, one of the metaheuristic methods, Ant Colony Optimization (ACO method (Max-Min Ant System – MMAS, was used to solve the Non-Euclidean TSP, which consisted of sets of different count points coincidentally located on the surface of a sphere. In this study seven point sets were used which have different point count. The performance of the MMAS method solving Non-Euclidean TSP problem was demonstrated by different experiments. Also, the results produced by ACO are compared with Discrete Cuckoo Search Algorithm (DCS and Genetic Algorithm (GA that are in the literature. The experiments for TSP on a sphere, show that ACO’s average results were better than the GA’s average results and also best results of ACO successful than the DCS.

  19. A colony-level response to disease control in a leaf-cutting ant

    Science.gov (United States)

    Hart, Adam; Bot, A. N. M.; Brown, Mark

    2002-03-01

    Parasites and pathogens often impose significant costs on their hosts. This is particularly true for social organisms, where the genetic structure of groups and the accumulation of contaminated waste facilitate disease transmission. In response, hosts have evolved many mechanisms of defence against parasites. Here we present evidence that Atta colombica, a leaf-cutting ant, may combat Escovopsis, a dangerous parasite of Atta's garden fungus, through a colony-level behavioural response. In A. colombica, garden waste is removed from within the colony and transported to the midden - an external waste dump - where it is processed by a group of midden workers. We found that colonies infected with Escovopsis have higher numbers of workers on the midden, where Escovopsis is deposited. Further, midden workers are highly effective in dispersing newly deposited waste away from the dumping site. Thus, the colony-level task allocation strategies of the Atta superorganism may change in response to the threat of disease to a third, essential party.

  20. GIS-BASED ROUTE FINDING USING ANT COLONY OPTIMIZATION AND URBAN TRAFFIC DATA FROM DIFFERENT SOURCES

    Directory of Open Access Journals (Sweden)

    M. Davoodi

    2015-12-01

    Full Text Available Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD, Automatic Number Plate Recognition (ANPR, Floating Car Data (FCD, VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

  1. Gis-Based Route Finding Using ANT Colony Optimization and Urban Traffic Data from Different Sources

    Science.gov (United States)

    Davoodi, M.; Mesgari, M. S.

    2015-12-01

    Nowadays traffic data is obtained from multiple sources including GPS, Video Vehicle Detectors (VVD), Automatic Number Plate Recognition (ANPR), Floating Car Data (FCD), VANETs, etc. All such data can be used for route finding. This paper proposes a model for finding the optimum route based on the integration of traffic data from different sources. Ant Colony Optimization is applied in this paper because the concept of this method (movement of ants in a network) is similar to urban road network and movements of cars. The results indicate that this model is capable of incorporating data from different sources, which may even be inconsistent.

  2. Ant colony optimisation of decision tree and contingency table models for the discovery of gene-gene interactions.

    Science.gov (United States)

    Sapin, Emmanuel; Keedwell, Ed; Frayling, Tim

    2015-12-01

    In this study, ant colony optimisation (ACO) algorithm is used to derive near-optimal interactions between a number of single nucleotide polymorphisms (SNPs). This approach is used to discover small numbers of SNPs that are combined into a decision tree or contingency table model. The ACO algorithm is shown to be very robust as it is proven to be able to find results that are discriminatory from a statistical perspective with logical interactions, decision tree and contingency table models for various numbers of SNPs considered in the interaction. A large number of the SNPs discovered here have been already identified in large genome-wide association studies to be related to type II diabetes in the literature, lending additional confidence to the results.

  3. Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

    OpenAIRE

    Morteza Atabati; Kobra Zarei; Azam Borhani

    2016-01-01

    Quantitative structure–property relationship (QSPR) studies based on ant colony optimization (ACO) were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 des...

  4. Stable isotope enrichment in laboratory ant colonies: effects of colony age, metamorphosis, diet, and fat storage

    Science.gov (United States)

    Ecologists use stable isotopes to infer diets and trophic levels of animals in food webs, yet some assumptions underlying these inferences have not been thoroughly tested. We used laboratory-reared colonies of Solenopsis invicta Buren (Formicidae: Solenopsidini) to test the effects of metamorphosis,...

  5. Energy Efficiency Performance Improvements for Ant-Based Routing Algorithm in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Adamu Murtala Zungeru

    2013-01-01

    Full Text Available The main problem for event gathering in wireless sensor networks (WSNs is the restricted communication range for each node. Due to the restricted communication range and high network density, event forwarding in WSNs is very challenging and requires multihop data forwarding. Currently, the energy-efficient ant based routing (EEABR algorithm, based on the ant colony optimization (ACO metaheuristic, is one of the state-of-the-art energy-aware routing protocols. In this paper, we propose three improvements to the EEABR algorithm to further improve its energy efficiency. The improvements to the original EEABR are based on the following: (1 a new scheme to intelligently initialize the routing tables giving priority to neighboring nodes that simultaneously could be the destination, (2 intelligent update of routing tables in case of a node or link failure, and (3 reducing the flooding ability of ants for congestion control. The energy efficiency improvements are significant particularly for dynamic routing environments. Experimental results using the RMASE simulation environment show that the proposed method increases the energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR without incurring a significant increase in complexity. The method is also compared and found to also outperform other swarm-based routing protocols such as sensor-driven and cost-aware ant routing (SC and Beesensor.

  6. A nuclear reactor core fuel reload optimization using Artificial-Ant-Colony Connective Networks

    International Nuclear Information System (INIS)

    Lima, Alan M.M. de; Schirru, Roberto

    2005-01-01

    A Pressurized Water Reactor core must be reloaded every time the fuel burnup reaches a level when it is not possible to sustain nominal power operation. The nuclear core fuel reload optimization consists in finding a burned-up and fresh-fuel-assembly pattern that maximizes the number of full operational days. This problem is NP-hard, meaning that complexity grows exponentially with the number of fuel assemblies in the core. Besides that, the problem is non-linear and its search space is highly discontinual and multimodal. In this work a parallel computational system based on Ant Colony System (ACS) called Artificial-Ant-Colony Networks is introduced to solve the nuclear reactor core fuel reload optimization problem. ACS is a system based on artificial agents that uses the reinforcement learning technique and was originally developed to solve the Traveling Salesman Problem, which is conceptually similar to the nuclear fuel reload problem. (author)

  7. Optimal Grid Scheduling Using Improved Artificial Bee Colony Algorithm

    OpenAIRE

    T. Vigneswari; M. A. Maluk Mohamed

    2015-01-01

    Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Hete...

  8. Efficacy of simulated barrier treatments against laboratory colonies of Pharaoh ant.

    Science.gov (United States)

    Buczkowski, Grzegorz; Scharf, Michael E; Ratliff, Catina R; Bennett, Gary W

    2005-04-01

    Five selected insecticides were applied to four substrates and evaluated in laboratory studies for repellency and toxicity against the Pharaoh ant, Monomorium pharaonis (L.). We tested both repellent and nonrepellent formulations on outdoor (concrete and mulch) and indoor (ceramic and vinyl) substrates. Repellency was evaluated using a behavioral bioassay in which colonies were given a choice to leave the treated zone and move into empty nests provided in the untreated zone. We used a novel experimental design whereby ants walked on a Slinky coil suspended from a metal support frame, thus permitting a long foraging distance with a minimum use of space and resources. Cypermethrin, a repellent pyrethroid insecticide, resulted in colony budding, although the response was delayed. Toxicity of insecticides was evaluated as worker, queen, and brood mortality. The most effective treatment was fipronil, which provided 100% reduction in pretreatment activity by 2 d posttreatment on both concrete and mulch. Chlorfenapyr was highly effective on both outdoor and indoor substrates. Significant substrate effects were observed with insecticides applied to nonabsorbent substrates (ceramic tile), which performed better than insecticides applied to absorbent substrates (vinyl tile). Other highly absorbent materials (mulch and concrete), however, did not reduce insecticide efficacy. This is because ants relocated nests into and/or under these attractive nesting materials, thus increasing their exposure to toxic insecticide residues. Our results demonstrate efficacy of nonrepellent liquid insecticides as indoor treatments for the control of Pharaoh ants and possibly as exterior perimeter treatments.

  9. Monomorphic ants undergo within-colony morphological changes along the metal-pollution gradient.

    Science.gov (United States)

    Grześ, Irena M; Okrutniak, Mateusz; Woch, Marcin W

    2015-04-01

    In ants, intra and inter-colony variation in body size can be considerable, even in monomorphic species. It has been previously shown that size-related parameters can be environmentally sensitive. The shape of the body size distribution curve is, however, rarely investigated. In this study, we measured head widthes of the black garden ant Lasius niger workers using digital methods. The ants were sampled from 51 colonies originating from 19 sites located along a metal pollution gradient, established in a former mining area in Poland. Total zinc concentrations in random samples of small invertebrates were used as a measure of site pollution levels. We found that the skewness of head size distribution grows significantly in line with the pollution level of the site, ranging from values slightly below zero (about -0.5) in the least polluted site up to a positive value (about 1.5) in the most polluted site. This result indicates that the frequency of small ants grows as pollution levels increase. The coefficient of variation, as well as the measures of central tendency, was not related to the pollution level. Four hypotheses explaining the obtained results are proposed. The bias towards the higher frequency of small workers may result from energy limitation and/or metal toxicity, but may also have an adaptive function.

  10. Multi-objective ant algorithm for wireless sensor network positioning

    International Nuclear Information System (INIS)

    Fidanova, S.; Shindarov, M.; Marinov, P.

    2013-01-01

    It is impossible to imagine our modern life without telecommunications. Wireless networks are a part of telecommunications. Wireless sensor networks (WSN) consist of spatially distributed sensors, which communicate in wireless way. This network monitors physical or environmental conditions. The objective is the full coverage of the monitoring region and less energy consumption of the network. The most appropriate approach to solve the problem is metaheuristics. In this paper the full coverage of the area is treated as a constrain. The objectives which are optimized are a minimal number of sensors and energy (lifetime) of the network. We apply multi-objective Ant Colony Optimization to solve this important telecommunication problem. We chose MAX-MIN Ant System approach, because it is proven to converge to the global optima

  11. Blending of heritable recognition cues among ant nestmates creates distinct colony gestalt odours but prevents within-colony nepotism.

    Science.gov (United States)

    van Zweden, J S; Brask, J B; Christensen, J H; Boomsma, J J; Linksvayer, T A; d'Ettorre, P

    2010-07-01

    The evolution of sociality is facilitated by the recognition of close kin, but if kin recognition is too accurate, nepotistic behaviour within societies can dissolve social cohesion. In social insects, cuticular hydrocarbons act as nestmate recognition cues and are usually mixed among colony members to create a Gestalt odour. Although earlier studies have established that hydrocarbon profiles are influenced by heritable factors, transfer among nestmates and additional environmental factors, no studies have quantified these relative contributions for separate compounds. Here, we use the ant Formica rufibarbis in a cross-fostering design to test the degree to which hydrocarbons are heritably synthesized by young workers and transferred by their foster workers. Bioassays show that nestmate recognition has a significant heritable component. Multivariate quantitative analyses based on 38 hydrocarbons reveal that a subset of branched alkanes are heritably synthesized, but that these are also extensively transferred among nestmates. In contrast, especially linear alkanes are less heritable and little transferred; these are therefore unlikely to act as cues that allow within-colony nepotistic discrimination or as nestmate recognition cues. These results indicate that heritable compounds are suitable for establishing a genetic Gestalt for efficient nestmate recognition, but that recognition cues within colonies are insufficiently distinct to allow nepotistic kin discrimination.

  12. Algorithm of Particle Data Association for SLAM Based on Improved Ant Algorithm

    Directory of Open Access Journals (Sweden)

    KeKe Gen

    2015-01-01

    Full Text Available The article considers a problem of data association algorithm for simultaneous localization and mapping guidelines in determining the route of unmanned aerial vehicles (UAVs. Currently, these equipments are already widely used, but mainly controlled from the remote operator. An urgent task is to develop a control system that allows for autonomous flight. Algorithm SLAM (simultaneous localization and mapping, which allows to predict the location, speed, the ratio of flight parameters and the coordinates of landmarks and obstacles in an unknown environment, is one of the key technologies to achieve real autonomous UAV flight. The aim of this work is to study the possibility of solving this problem by using an improved ant algorithm.The data association for SLAM algorithm is meant to establish a matching set of observed landmarks and landmarks in the state vector. Ant algorithm is one of the widely used optimization algorithms with positive feedback and the ability to search in parallel, so the algorithm is suitable for solving the problem of data association for SLAM. But the traditional ant algorithm in the process of finding routes easily falls into local optimum. Adding random perturbations in the process of updating the global pheromone to avoid local optima. Setting limits pheromone on the route can increase the search space with a reasonable amount of calculations for finding the optimal route.The paper proposes an algorithm of the local data association for SLAM algorithm based on an improved ant algorithm. To increase the speed of calculation, local data association is used instead of the global data association. The first stage of the algorithm defines targets in the matching space and the observed landmarks with the possibility of association by the criterion of individual compatibility (IC. The second stage defines the matched landmarks and their coordinates using improved ant algorithm. Simulation results confirm the efficiency and

  13. Colony kin structure and breeding system in the ant genus Plagiolepis.

    Science.gov (United States)

    Thurin, N; Sery, N; Guimbretiere, R; Aron, S

    2011-08-01

    Relatedness is a central parameter in the evolution of sociality, because kin selection theory assumes that individuals involved in altruistic interactions are related. At least three reproductive characteristics are known to profoundly affect colony kin structure in social insects: the number of reproductive queens per colony, the relatedness among breeding queens and queen mating frequency. Both the occurrence of multiple queens (polygyny) and multiple mating (polyandry) decrease within-colony relatedness, while mating among sibs increases relatedness between the workers and the brood they rear. Using DNA microsatellites, we performed a detailed genetic analysis of the colony kin structure and breeding system in three ant species belonging to the genus Plagiolepis: P. schmitzii, P. taurica and P. maura. Our data show that queens of the three species mate multiply: queens of P. maura mate with 1-2 males, queens of P. taurica with 3-11 males and queens of P. schmitzii may have 1-14 different mates. Moreover, colonies are headed by multiple queens: P. taurica and P. maura are facultatively polygynous, while P. schmitzii is obligately polygynous. Despite polyandry and polygyny, relatedness within colonies remains high because all species are characterized by sib-mating, with a fixation index F(it) = 0.25 in P. taurica, 0.24 in P. schmitzii and 0.26 in P. maura, and because the male mates of a queen are on average closely related. © 2011 Blackwell Publishing Ltd.

  14. A Simple and Efficient Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yunfeng Xu

    2013-01-01

    Full Text Available Artificial bee colony (ABC is a new population-based stochastic algorithm which has shown good search abilities on many optimization problems. However, the original ABC shows slow convergence speed during the search process. In order to enhance the performance of ABC, this paper proposes a new artificial bee colony (NABC algorithm, which modifies the search pattern of both employed and onlooker bees. A solution pool is constructed by storing some best solutions of the current swarm. New candidate solutions are generated by searching the neighborhood of solutions randomly chosen from the solution pool. Experiments are conducted on a set of twelve benchmark functions. Simulation results show that our approach is significantly better or at least comparable to the original ABC and seven other stochastic algorithms.

  15. Friends and foes from an ant brain's point of view--neuronal correlates of colony odors in a social insect.

    Science.gov (United States)

    Brandstaetter, Andreas Simon; Rössler, Wolfgang; Kleineidam, Christoph Johannes

    2011-01-01

    Successful cooperation depends on reliable identification of friends and foes. Social insects discriminate colony members (nestmates/friends) from foreign workers (non-nestmates/foes) by colony-specific, multi-component colony odors. Traditionally, complex processing in the brain has been regarded as crucial for colony recognition. Odor information is represented as spatial patterns of activity and processed in the primary olfactory neuropile, the antennal lobe (AL) of insects, which is analogous to the vertebrate olfactory bulb. Correlative evidence indicates that the spatial activity patterns reflect odor-quality, i.e., how an odor is perceived. For colony odors, alternatively, a sensory filter in the peripheral nervous system was suggested, causing specific anosmia to nestmate colony odors. Here, we investigate neuronal correlates of colony odors in the brain of a social insect to directly test whether they are anosmic to nestmate colony odors and whether spatial activity patterns in the AL can predict how odor qualities like "friend" and "foe" are attributed to colony odors. Using ant dummies that mimic natural conditions, we presented colony odors and investigated their neuronal representation in the ant Camponotus floridanus. Nestmate and non-nestmate colony odors elicited neuronal activity: In the periphery, we recorded sensory responses of olfactory receptor neurons (electroantennography), and in the brain, we measured colony odor specific spatial activity patterns in the AL (calcium imaging). Surprisingly, upon repeated stimulation with the same colony odor, spatial activity patterns were variable, and as variable as activity patterns elicited by different colony odors. Ants are not anosmic to nestmate colony odors. However, spatial activity patterns in the AL alone do not provide sufficient information for colony odor discrimination and this finding challenges the current notion of how odor quality is coded. Our result illustrates the enormous challenge

  16. Dynamic Load Balancing Strategy for Cloud Computing with Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Ren Gao

    2015-11-01

    Full Text Available How to distribute and coordinate tasks in cloud computing is a challenging issue, in order to get optimal resource utilization and avoid overload. In this paper, we present a novel approach on load balancing via ant colony optimization (ACO, for balancing the workload in a cloud computing platform dynamically. Two strategies, forward-backward ant mechanism and max-min rules, are introduced to quickly find out the candidate nodes for load balancing. We formulate pheromone initialization and pheromone update according to physical resources under the cloud computing environment, including pheromone evaporation, incentive, and punishment rules, etc. Combined with task execution prediction, we define the moving probability of ants in two ways, that is, whether the forward ant meets the backward ant, or not, in the neighbor node, with the aim of accelerating searching processes. Simulations illustrate that the proposed strategy can not only provide dynamic load balancing for cloud computing with less searching time, but can also get high network performance under medium and heavily loaded contexts.

  17. Colony structure and spatial partitioning of cavity dwelling ant species in nuts of eastern US forest floors

    Science.gov (United States)

    Nut-bearing trees create islands of high efficiency, low cost housing opportunities for ant colonies. Fallen nuts in leaf litter from previous seasons provide ready-made nest sites for cavity dwelling ant species, as well as affording protection from the elements. Suitable nuts for nests require an ...

  18. Arboreal ant colonies as 'hot-points' of cryptic diversity for myrmecophiles: the weaver ant Camponotus sp. aff. textor and its interaction network with its associates.

    Directory of Open Access Journals (Sweden)

    Gabriela Pérez-Lachaud

    Full Text Available INTRODUCTION: Systematic surveys of macrofaunal diversity within ant colonies are lacking, particularly for ants nesting in microhabitats that are difficult to sample. Species associated with ants are generally small and rarely collected organisms, which makes them more likely to be unnoticed. We assumed that this tendency is greater for arthropod communities in microhabitats with low accessibility, such as those found in the nests of arboreal ants that may constitute a source of cryptic biodiversity. MATERIALS AND METHODS: We investigated the invertebrate diversity associated with an undescribed, but already threatened, Neotropical Camponotus weaver ant. As most of the common sampling methods used in studies of ant diversity are not suited for evaluating myrmecophile diversity within ant nests, we evaluated the macrofauna within ant nests through exhaustive colony sampling of three nests and examination of more than 80,000 individuals. RESULTS: We identified invertebrates from three classes belonging to 18 taxa, some of which were new to science, and recorded the first instance of the co-occurrence of two brood parasitoid wasp families attacking the same ant host colony. This diversity of ant associates corresponded to a highly complex interaction network. Agonistic interactions prevailed, but the prevalence of myrmecophiles was remarkably low. CONCLUSIONS: Our data support the hypothesis of the evolution of low virulence in a variety of symbionts associated with large insect societies. Because most myrmecophiles found in this work are rare, strictly specific, and exhibit highly specialized biology, the risk of extinction for these hitherto unknown invertebrates and their natural enemies is high. The cryptic, far unappreciated diversity within arboreal ant nests in areas at high risk of habitat loss qualifies these nests as 'hot-points' of biodiversity that urgently require special attention as a component of conservation and management

  19. Intraspecific competition affects population size and resource allocation in an ant dispersing by colony fission.

    Science.gov (United States)

    Boulay, Raphaël; Galarza, Juan A; Chéron, Blandine; Hefetz, Abraham; Lenoir, Alain; van Oudenhove, Louise; Cerdá, Xim

    2010-11-01

    Intraspecific competition is a pervasive phenomenon with important ecological and evolutionary consequences, yet its effect in natural populations remains controversial. Although numerous studies suggest that in many cases populations across all organisms are limited by density-dependent processes, this conclusion often relies on correlative data. Here, using an experimental approach, we examined the effect of intraspecific competition on population regulation of the ant Aphaenogaster senilis. In this species females are philopatric while males disperse by flying over relatively long distances. All colonies were removed from 15 experimental plots, except for one focal colony in each plot, while 15 other plots remained unmanipulated. After the first reproductive season, nest density in the experimental plots returned to a level nonsignificantly different from that in the control plots, which was not expected if the populations were indeed regulated by density-independent phenomena. In both the control plots and the experimental plots colonies remained overdispersed throughout the experiment, suggesting colony mutual exclusion. Nests outside the plots rapidly extended their foraging span, but we did not detect any significant inward migration into the experimental plots. Experimental reduction in density did not significantly affect the focal colonies' biomass, measured just before the first reproductive season. However, the ratio of males to workers-pupae biomasses was smaller in experimental plots, suggesting that colonies there had redirected part of the resources normally allocated to male production to the production instead of new workers. Microsatellite analysis indicated that, after the reproductive season, many colonies in the experimental plots were headed by a young queen that was the mother of the brood but not of the old workers, indicating that reduction in colony density stimulated fission of the remaining colonies. Finally, at the end of the

  20. Uncovering interactions in Plackett-Burman screening designs applied to analytical systems. A Monte Carlo ant colony optimization approach.

    Science.gov (United States)

    Olivieri, Alejandro C; Magallanes, Jorge F

    2012-08-15

    Screening of relevant factors using Plackett-Burman designs is usual in analytical chemistry. It relies on the assumption that factor interactions are negligible; however, failure of recognizing such interactions may lead to incorrect results. Factor associations can be revealed by feature selection techniques such as ant colony optimization. This method has been combined with a Monte Carlo approach, developing a new algorithm for assessing both main and interaction terms when analyzing the influence of experimental factors through a Plackett-Burman design of experiments. The results for both simulated and analytically relevant experimental systems show excellent agreement with previous approaches, highlighting the importance of considering potential interactions when conducting a screening search. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. Multiobjective optimal placement of switches and protective devices in electric power distribution systems using ant colony optimization

    Energy Technology Data Exchange (ETDEWEB)

    Tippachon, Wiwat; Rerkpreedapong, Dulpichet [Department of Electrical Engineering, Kasetsart University, 50 Phaholyothin Rd., Ladyao, Jatujak, Bangkok 10900 (Thailand)

    2009-07-15

    This paper presents a multiobjective optimization methodology to optimally place switches and protective devices in electric power distribution networks. Identifying the type and location of them is a combinatorial optimization problem described by a nonlinear and nondifferential function. The multiobjective ant colony optimization (MACO) has been applied to this problem to minimize the total cost while simultaneously minimize two distribution network reliability indices including system average interruption frequency index (SAIFI) and system interruption duration index (SAIDI). Actual distribution feeders are used in the tests, and test results have shown that the algorithm can determine the set of optimal nondominated solutions. It allows the utility to obtain the optimal type and location of devices to achieve the best system reliability with the lowest cost. (author)

  2. Successful transmission of Solenopsis invicta virus 3 to Solenopsis invicta fire ant colonies in oil, sugar, and cricket bait formulations

    Science.gov (United States)

    Tests were conducted to evaluate whether Solenopsis invicta virus 3 (SINV-3) could be delivered in various bait formulations to fire ant colonies and measure the corresponding colony health changes associated with virus infection in Solenopsis invicta. Three bait formulations (10% sugar solution, c...

  3. Long-term efficacy of two cricket and two liver diets for rearing laboratory fire ant colonies (Hymenoptera: Formicidae: Solenopsis Invicta)

    Science.gov (United States)

    Effective diets are necessary for many kinds of laboratory studies of ants. We conducted a year-long study of imported fire ant colonies reared on either chicken liver, beef liver, banded crickets, or domestic crickets all with a sugar water supplement. Fire ant colonies thrived on diets of sugar ...

  4. Lock-picks: fungal infection facilitates the intrusion of strangers into ant colonies

    Science.gov (United States)

    Csata, Enikő; Timuş, Natalia; Witek, Magdalena; Casacci, Luca Pietro; Lucas, Christophe; Bagnères, Anne-Geneviève; Sztencel-Jabłonka, Anna; Barbero, Francesca; Bonelli, Simona; Rákosy, László; Markó, Bálint

    2017-01-01

    Studies investigating host-parasite systems rarely deal with multispecies interactions, and mostly explore impacts on hosts as individuals. Much less is known about the effects at colony level, when parasitism involves host organisms that form societies. We surveyed the effect of an ectoparasitic fungus, Rickia wasmannii, on kin-discrimination abilities of its host ant, Myrmica scabrinodis, identifying potential consequences at social level and subsequent changes in colony infiltration success of other organisms. Analyses of cuticular hydrocarbons (CHCs), known to be involved in insects’ discrimination processes, revealed variations in chemical profiles correlated with the infection status of the ants, that could not be explained by genetic variation tested by microsatellites. In behavioural assays, fungus-infected workers were less aggressive towards both non-nestmates and unrelated queens, enhancing the probability of polygyny. Likewise, parasitic larvae of Maculinea butterflies had a higher chance of adoption by infected colonies. Our study indicates that pathogens can modify host recognition abilities, making the society more prone to accept both conspecific and allospecific organisms. PMID:28402336

  5. Hybrid Bee Ant Colony Algorithm for Effective Load Balancing And ...

    African Journals Online (AJOL)

    PROF. OLIVER OSUAGWA

    Cloud Computing is new paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). Cloud. Computing is a new ...

  6. Hybrid Bee Ant Colony Algorithm for Effective Load Balancing And ...

    African Journals Online (AJOL)

    Cloud Computing is new paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). Cloud Computing is a new ...

  7. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    Science.gov (United States)

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  8. A Developed Artificial Bee Colony Algorithm Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Ye Jin

    2018-04-01

    Full Text Available The Artificial Bee Colony (ABC algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.

  9. Colony-level behavioural variation correlates with differences in expression of the foraging gene in red imported fire ants.

    Science.gov (United States)

    Bockoven, Alison A; Coates, Craig J; Eubanks, Micky D

    2017-11-01

    Among social insects, colony-level variation is likely to be widespread and has significant ecological consequences. Very few studies, however, have documented how genetic factors relate to behaviour at the colony level. Differences in expression of the foraging gene have been associated with differences in foraging and activity of a wide variety of organisms. We quantified expression of the red imported fire ant foraging gene (sifor) in workers from 21 colonies collected across the natural range of Texas fire ant populations, but maintained under standardized, environmentally controlled conditions. Colonies varied significantly in their behaviour. The most active colonies had up to 10 times more active foragers than the least active colony and more than 16 times as many workers outside the nest. Expression differences among colonies correlated with this colony-level behavioural variation. Colonies with higher sifor expression in foragers had, on average, significantly higher foraging activity, exploratory activity and recruitment to nectar than colonies with lower expression. Expression of sifor was also strongly correlated with worker task (foraging vs. working in the interior of the nest). These results provide insight into the genetic and physiological processes underlying collective differences in social behaviour. Quantifying variation in expression of the foraging gene may provide an important tool for understanding and predicting the ecological consequences of colony-level behavioural variation. © 2017 John Wiley & Sons Ltd.

  10. Social transfer of pathogenic fungus promotes active immunisation in ant colonies.

    Directory of Open Access Journals (Sweden)

    Matthias Konrad

    Full Text Available Due to the omnipresent risk of epidemics, insect societies have evolved sophisticated disease defences at the individual and colony level. An intriguing yet little understood phenomenon is that social contact to pathogen-exposed individuals reduces susceptibility of previously naive nestmates to this pathogen. We tested whether such social immunisation in Lasius ants against the entomopathogenic fungus Metarhizium anisopliae is based on active upregulation of the immune system of nestmates following contact to an infectious individual or passive protection via transfer of immune effectors among group members--that is, active versus passive immunisation. We found no evidence for involvement of passive immunisation via transfer of antimicrobials among colony members. Instead, intensive allogrooming behaviour between naive and pathogen-exposed ants before fungal conidia firmly attached to their cuticle suggested passage of the pathogen from the exposed individuals to their nestmates. By tracing fluorescence-labelled conidia we indeed detected frequent pathogen transfer to the nestmates, where they caused low-level infections as revealed by growth of small numbers of fungal colony forming units from their dissected body content. These infections rarely led to death, but instead promoted an enhanced ability to inhibit fungal growth and an active upregulation of immune genes involved in antifungal defences (defensin and prophenoloxidase, PPO. Contrarily, there was no upregulation of the gene cathepsin L, which is associated with antibacterial and antiviral defences, and we found no increased antibacterial activity of nestmates of fungus-exposed ants. This indicates that social immunisation after fungal exposure is specific, similar to recent findings for individual-level immune priming in invertebrates. Epidemiological modeling further suggests that active social immunisation is adaptive, as it leads to faster elimination of the disease and lower

  11. Genetic regulation of colony social organization in fire ants: an integrative overview.

    Science.gov (United States)

    Gotzek, Dietrich; Ross, Kenneth G

    2007-09-01

    Expression of colony social organization in fire ants appears to be under the control of a single Mendelian factor of large effect. Variation in colony queen number in Solenopsis invicta and its relatives is associated with allelic variation at the gene Gp-9, but not with variation at other unlinked genes; workers regulate queen identity and number on the basis of Gp-9 genotypic compatibility. Nongenetic factors, such as prior social experience, queen reproductive status, and local environment, have negligible effects on queen numbers which illustrates the nearly complete penetrance of Gp-9. As predicted, queen number can be manipulated experimentally by altering worker Gp-9 genotype frequencies. The Gp-9 allele lineage associated with polygyny in South American fire ants has been retained across multiple speciation events, which may signal the action of balancing selection to maintain social polymorphism in these species. Moreover, positive selection is implicated in driving the molecular evolution of Gp-9 in association with the origin of polygyny. The identity of the product of Gp-9 as an odorant-binding protein suggests plausible scenarios for its direct involvement in the regulation of queen number via a role in chemical communication. While these and other lines of evidence show that Gp-9 represents a legitimate candidate gene of major effect, studies aimed at determining (i) the biochemical pathways in which GP-9 functions; (ii) the phenotypic effects of molecular variation at Gp-9 and other pathway genes; and (iii) the potential involvement of genes in linkage disequilibrium with Gp-9 are needed to elucidate the genetic architecture underlying social organization in fire ants. Information that reveals the links between molecular variation, individual phenotype, and colony-level behaviors, combined with behavioral models that incorporate details of the chemical communication involved in regulating queen number, will yield a novel integrated view of the

  12. Optimization of travel salesman problem using the ant colony system and Greedy search

    International Nuclear Information System (INIS)

    Esquivel E, J.; Ordonez A, A.; Ortiz S, J. J.

    2008-01-01

    In this paper we present some results obtained during the development of optimization systems that can be used to design refueling and patterns of control rods in a BWR. These systems use ant colonies and Greedy search. The first phase of this project is to be familiar with these optimization techniques applied to the problem of travel salesman problem (TSP). The utility of TSP study is that, like the refueling design and pattern design of control rods are problems of combinative optimization. Even, the similarity with the problem of the refueling design is remarkable. It is presented some results for the TSP with the 32 state capitals of Mexico country. (Author)

  13. Social influence on age and reproduction: reduced lifespan and fecundity in multi-queen ant colonies.

    Science.gov (United States)

    Schrempf, A; Cremer, S; Heinze, J

    2011-07-01

    Evolutionary theories of ageing predict that life span increases with decreasing extrinsic mortality, and life span variation among queens in ant species seems to corroborate this prediction: queens, which are the only reproductive in a colony, live much longer than queens in multi-queen colonies. The latter often inhabit ephemeral nest sites and accordingly are assumed to experience a higher mortality risk. Yet, all prior studies compared queens from different single- and multi-queen species. Here, we demonstrate an effect of queen number on longevity and fecundity within a single, socially plastic species, where queens experience the similar level of extrinsic mortality. Queens from single- and two-queen colonies had significantly longer lifespan and higher fecundity than queens living in associations of eight queens. As queens also differ neither in morphology nor the mode of colony foundation, our study shows that the social environment itself strongly affects ageing rate. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

  14. Role of relative humidity in colony founding and queen survivorship in two carpenter ant species.

    Science.gov (United States)

    Mankowski, Mark E; Morrell, J J

    2011-06-01

    Conditions necessary for optimal colony foundation in two carpenter ant species, Camponotus modoc Wheeler and Camponotus vicinus Mayr, were studied. Camponotus modoc and C. vicinus queens were placed in Douglas-fir, Pseudotsuga menziesii (Mirb. Franco) and Styrofoam blocks conditioned in sealed chambers at 70, 80, or 100% RH. Nanitic workers produced after 12 wk were used to assess the effects of substrate and moisture content on colony initiation. Queens of C. vicinus in Douglas-fir and Styrofoam produced worker numbers that did not differ significantly with moisture content; however, the number of colonies initiated by C. modoc differed significantly with moisture content. The results indicate that colony founding in C. vicinus is less sensitive to moisture content than C. modoc for Douglas-fir and Styrofoam. In another test, groups of queens of each species were exposed to 20, 50, 70, and 100% RH and the time until 50% mortality occurred was recorded for each species. C. vicinus lived significantly longer at each of the test humidities than C. modoc, suggesting that the former species is adapted to better survive under xeric conditions.

  15. Quantifying the effect of colony size and food distribution on harvester ant foraging.

    Directory of Open Access Journals (Sweden)

    Tatiana P Flanagan

    Full Text Available Desert seed-harvester ants, genus Pogonomyrmex, are central place foragers that search for resources collectively. We quantify how seed harvesters exploit the spatial distribution of seeds to improve their rate of seed collection. We find that foraging rates are significantly influenced by the clumpiness of experimental seed baits. Colonies collected seeds from larger piles faster than randomly distributed seeds. We developed a method to compare foraging rates on clumped versus random seeds across three Pogonomyrmex species that differ substantially in forager population size. The increase in foraging rate when food was clumped in larger piles was indistinguishable across the three species, suggesting that species with larger colonies are no better than species with smaller colonies at collecting clumped seeds. These findings contradict the theoretical expectation that larger groups are more efficient at exploiting clumped resources, thus contributing to our understanding of the importance of the spatial distribution of food sources and colony size for communication and organization in social insects.

  16. Study on bi-directional pedestrian movement using ant algorithms

    International Nuclear Information System (INIS)

    Gokce, Sibel; Kayacan, Ozhan

    2016-01-01

    A cellular automata model is proposed to simulate bi-directional pedestrian flow. Pedestrian movement is investigated by using ant algorithms. Ants communicate with each other by dropping a chemical, called a pheromone, on the substrate while crawling forward. Similarly, it is considered that oppositely moving pedestrians drop ‘visual pheromones’ on their way and the visual pheromones might cause attractive or repulsive interactions. This pheromenon is introduced into modelling the pedestrians’ walking preference. In this way, the decision-making process of pedestrians will be based on ‘the instinct of following’. At some densities, the relationships of velocity–density and flux–density are analyzed for different evaporation rates of visual pheromones. Lane formation and phase transition are observed for certain evaporation rates of visual pheromones. (paper)

  17. Multiple Input Delays Estimation Using an Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Wei-Der Chang

    2013-01-01

    Full Text Available This paper focuses on the time delay estimation of the system described in the form of discrete-time state equation with multiple input delays. To estimate the input delays, a new evolutionary computation called the artificial bee colony (ABC algorithm is utilized. This algorithm is originally motivated from the social behaviors of honeybee organization, and it has been proven to be a powerful means for solving the optimized problem. Based on the proposed algorithm, the unknown system input delays can be further solved by minimizing a quadratic cost function of the system. Two illustrative examples are provided to verify the potential of the presented method in the time delay estimation. Some simulations containing different initial condition examinations and appearance of noises are further given. Numerical results show that the proposed method can do well in the multiple inputs delay estimation of discrete-time state equations.

  18. Incomplete homogenization of chemical recognition labels between Formica sanguinea and Formica rufa ants (Hymenoptera: Formicidae) living in a mixed colony.

    Science.gov (United States)

    Włodarczyk, Tomasz; Szczepaniak, Lech

    2014-01-01

    Formica sanguinea Latreille (Hymenoptera: Formicidae) is a slave-making species, i.e., it raids colonies of host species and pillages pupae, which are taken to develop into adult workers in a parasite colony. However, it has been unclear if the coexistence of F. sanguinea with slave workers requires uniformity of cuticular hydrocarbons (CHCs), among which those other than n-alkanes are believed to be the principal nestmate recognition cues utilized by ants. In this study, a mixed colony (MC) of F. sanguinea and Formica rufa L. as a slave species was used to test the hypothesis that CHCs are exchanged between the species. Chemical analysis of hexane extracts from ants' body surfaces provided evidence for interspecific exchange of alkenes and methyl-branched alkanes. This result was confirmed by behavioral tests during which ants exhibited hostility toward conspecific individuals from the MC but not toward ones from homospecific colonies of their own species. However, it seems that species-specific differences in chemical recognition labels were not eliminated completely because ants from the MC were treated differently depending on whether they were con- or allospecific to the individuals whose behavioral reactions were tested. These findings are discussed in the context of mechanisms of colony's odor formation and effective integration of slaves into parasite colony. © The Author 2014. Published by Oxford University Press on behalf of the Entomological Society of America.

  19. An Improved Ant Colony Optimization Approach for Optimization of Process Planning

    Directory of Open Access Journals (Sweden)

    JinFeng Wang

    2014-01-01

    Full Text Available Computer-aided process planning (CAPP is an important interface between computer-aided design (CAD and computer-aided manufacturing (CAM in computer-integrated manufacturing environments (CIMs. In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs. A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

  20. Effects of a juvenile hormone analogue pyriproxyfen on monogynous and polygynous colonies of the Pharaoh ant Monomorium pharaonis (Hymenoptera: Formicidae).

    Science.gov (United States)

    Tay, J W; Lee, C Y

    2015-09-01

    To evaluate the effects of the juvenile hormone analogue pyriproxyfen on colonies of the Pharaoh ant Monomorium pharaonis (L.), peanut oil containing different concentrations (0.3, 0.6, or 0.9%) of pyriproxyfen was fed to monogynous (1 queen, 500 workers, and 0.1 g of brood) and polygynous (8 queens, 50 workers, and 0.1 g of brood) laboratory colonies of M. pharaonis. Due to its delayed activity, pyriproxyfen at all concentrations resulted in colony elimination. Significant reductions in brood volume were recorded at weeks 3 - 6, and complete brood mortality was observed at week 8 in all treated colonies. Brood mortality was attributed to the disruption of brood development and cessation of egg production by queens. All polygynous colonies exhibited significant reduction in the number of queens present at week 10 compared to week 1. Number of workers was significantly lower in all treated colonies compared to control colonies at week 8 due to old-age attrition of the workers without replacement. At least 98.67 ± 1.33% of workers were dead at week 10 in all treated colonies. Thus, treatment with slow acting pyriproxyfen at concentrations of 0.3 - 0.9% is an effective strategy for eliminating Pharaoh ant colonies.

  1. Estimating the net electricity energy generation and demand using the ant colony optimization approach. Case of Turkey

    International Nuclear Information System (INIS)

    Toksari, M. Duran

    2009-01-01

    This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear A COEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic A COEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios. (author)

  2. The effects of disturbance threat on leaf-cutting ant colonies: a laboratory study.

    Science.gov (United States)

    Norman, V C; Pamminger, T; Hughes, W O H

    2017-01-01

    The flexibility of organisms to respond plastically to their environment is fundamental to their fitness and evolutionary success. Social insects provide some of the most impressive examples of plasticity, with individuals exhibiting behavioral and sometimes morphological adaptations for their specific roles in the colony, such as large soldiers for nest defense. However, with the exception of the honey bee model organism, there has been little investigation of the nature and effects of environmental stimuli thought to instigate alternative phenotypes in social insects. Here, we investigate the effect of repeated threat disturbance over a prolonged (17 month) period on both behavioral and morphological phenotypes, using phenotypically plastic leaf-cutting ants ( Atta colombica ) as a model system. We found a rapid impact of threat disturbance on the behavioral phenotype of individuals within threat-disturbed colonies becoming more aggressive, threat responsive, and phototactic within as little as 2 weeks. We found no effect of threat disturbance on morphological phenotypes, potentially, because constraints such as resource limitation outweighed the benefit for colonies of producing larger individuals. The results suggest that plasticity in behavioral phenotypes can enable insect societies to respond to threats even when constraints prevent alteration of morphological phenotypes.

  3. High recombination frequency creates genotypic diversity in colonies of the leaf-cutting ant Acromyrmex echinatior

    DEFF Research Database (Denmark)

    Sirviö, A.; Gadau, J.; Rueppell, O.

    2006-01-01

    Honeybees are known to have genetically diverse colonies because queens mate with many males and the recombination rate is extremely high. Genetic diversity among social insect workers has been hypothesized to improve general performance of large and complex colonies, but this idea has not been...... tested in other social insects. Here, we present a linkage map and an estimate of the recombination rate for Acromyrmex echinatior, a leaf-cutting ant that resembles the honeybee in having multiple mating of queens and colonies of approximately the same size. A map of 145 AFLP markers in 22 linkage...... groups yielded a total recombinational size of 2076 cM and an inferred recombination rate of 161 kb cM-1 (or 6.2 cM Mb-1). This estimate is lower than in the honeybee but, as far as the mapping criteria can be compared, higher than in any other insect mapped so far. Earlier studies on A. echinatior have...

  4. Enhanced Ant Colony Optimization with Dynamic Mutation and Ad Hoc Initialization for Improving the Design of TSK-Type Fuzzy System

    Science.gov (United States)

    Liu, Yi-Ting

    2018-01-01

    This paper proposes an enhanced ant colony optimization with dynamic mutation and ad hoc initialization, ACODM-I, for improving the accuracy of Takagi-Sugeno-Kang- (TSK-) type fuzzy systems design. Instead of the generic initialization usually used in most population-based algorithms, ACODM-I proposes an ad hoc application-specific initialization for generating the initial ant solutions to improve the accuracy of fuzzy system design. The generated initial ant solutions are iteratively improved by a new approach incorporating the dynamic mutation into the existing continuous ACO (ACOR). The introduced dynamic mutation balances the exploration ability and convergence rate by providing more diverse search directions in the early stage of optimization process. Application examples of two zero-order TSK-type fuzzy systems for dynamic plant tracking control and one first-order TSK-type fuzzy system for the prediction of the chaotic time series have been simulated to validate the proposed algorithm. Performance comparisons with ACOR and different advanced algorithms or neural-fuzzy models verify the superiority of the proposed algorithm. The effects on the design accuracy and convergence rate yielded by the proposed initialization and introduced dynamic mutation have also been discussed and verified in the simulations. PMID:29568311

  5. Enhanced Ant Colony Optimization with Dynamic Mutation and Ad Hoc Initialization for Improving the Design of TSK-Type Fuzzy System

    Directory of Open Access Journals (Sweden)

    Chi-Chung Chen

    2018-01-01

    Full Text Available This paper proposes an enhanced ant colony optimization with dynamic mutation and ad hoc initialization, ACODM-I, for improving the accuracy of Takagi-Sugeno-Kang- (TSK- type fuzzy systems design. Instead of the generic initialization usually used in most population-based algorithms, ACODM-I proposes an ad hoc application-specific initialization for generating the initial ant solutions to improve the accuracy of fuzzy system design. The generated initial ant solutions are iteratively improved by a new approach incorporating the dynamic mutation into the existing continuous ACO (ACOR. The introduced dynamic mutation balances the exploration ability and convergence rate by providing more diverse search directions in the early stage of optimization process. Application examples of two zero-order TSK-type fuzzy systems for dynamic plant tracking control and one first-order TSK-type fuzzy system for the prediction of the chaotic time series have been simulated to validate the proposed algorithm. Performance comparisons with ACOR and different advanced algorithms or neural-fuzzy models verify the superiority of the proposed algorithm. The effects on the design accuracy and convergence rate yielded by the proposed initialization and introduced dynamic mutation have also been discussed and verified in the simulations.

  6. An artificial bee colony algorithm for uncertain portfolio selection.

    Science.gov (United States)

    Chen, Wei

    2014-01-01

    Portfolio selection is an important issue for researchers and practitioners. In this paper, under the assumption that security returns are given by experts' evaluations rather than historical data, we discuss the portfolio adjusting problem which takes transaction costs and diversification degree of portfolio into consideration. Uncertain variables are employed to describe the security returns. In the proposed mean-variance-entropy model, the uncertain mean value of the return is used to measure investment return, the uncertain variance of the return is used to measure investment risk, and the entropy is used to measure diversification degree of portfolio. In order to solve the proposed model, a modified artificial bee colony (ABC) algorithm is designed. Finally, a numerical example is given to illustrate the modelling idea and the effectiveness of the proposed algorithm.

  7. Friends and Foes from an Ant Brain's Point of View – Neuronal Correlates of Colony Odors in a Social Insect

    Science.gov (United States)

    Brandstaetter, Andreas Simon; Rössler, Wolfgang; Kleineidam, Christoph Johannes

    2011-01-01

    Background Successful cooperation depends on reliable identification of friends and foes. Social insects discriminate colony members (nestmates/friends) from foreign workers (non-nestmates/foes) by colony-specific, multi-component colony odors. Traditionally, complex processing in the brain has been regarded as crucial for colony recognition. Odor information is represented as spatial patterns of activity and processed in the primary olfactory neuropile, the antennal lobe (AL) of insects, which is analogous to the vertebrate olfactory bulb. Correlative evidence indicates that the spatial activity patterns reflect odor-quality, i.e., how an odor is perceived. For colony odors, alternatively, a sensory filter in the peripheral nervous system was suggested, causing specific anosmia to nestmate colony odors. Here, we investigate neuronal correlates of colony odors in the brain of a social insect to directly test whether they are anosmic to nestmate colony odors and whether spatial activity patterns in the AL can predict how odor qualities like “friend” and “foe” are attributed to colony odors. Methodology/Principal Findings Using ant dummies that mimic natural conditions, we presented colony odors and investigated their neuronal representation in the ant Camponotus floridanus. Nestmate and non-nestmate colony odors elicited neuronal activity: In the periphery, we recorded sensory responses of olfactory receptor neurons (electroantennography), and in the brain, we measured colony odor specific spatial activity patterns in the AL (calcium imaging). Surprisingly, upon repeated stimulation with the same colony odor, spatial activity patterns were variable, and as variable as activity patterns elicited by different colony odors. Conclusions Ants are not anosmic to nestmate colony odors. However, spatial activity patterns in the AL alone do not provide sufficient information for colony odor discrimination and this finding challenges the current notion of how odor

  8. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection

    Directory of Open Access Journals (Sweden)

    Zhiwen Liu

    2015-08-01

    Full Text Available Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM based on an ant colony optimization algorithm (ACO-RVM for gearboxes’ fault detection. RVM is a sparse probability model based on support vector machine (SVM. RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV.

  9. Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

    Science.gov (United States)

    Anam, S.

    2017-10-01

    Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

  10. Ant colony algorithm for analysis of gene interaction in high-dimensional association data Algoritmo colônia de formigas para análise de interação gênica em dados de associação de alta dimensão

    Directory of Open Access Journals (Sweden)

    Romdhane Rekaya

    2009-07-01

    Full Text Available In recent years there has been much focus on the use of single nucleotide polymorphism (SNP fine genome mapping to identify causative mutations for traits of interest; however, many studies focus only on the marginal effects of markers, ignoring potential gene interactions. Simulation studies have show that this approach may not be powerful enough to detect important loci when gene interactions are present. While several studies have examined potential gene interaction, they tend to focus on a small number of SNP markers. Given the prohibitive computation cost of modeling interactions in studies involving a large number SNP, methods need to be develop that can account for potential gene interactions in a computationally efficient manner. This study adopts a machine learning approach by adapting the ant colony optimization algorithm (ACA, coupled with logistic regression on haplotypes and genotypes, for association studies involving large numbers of SNP markers. The proposed method is compared to haplotype analysis, implemented using a sliding window (SW/H, and single locus genotype association (RG. Each algorithm was evaluated using a binary trait simulated using an epistatic model and HapMap ENCODE genotype data. Results show that the ACA outperformed SW/H and RG under all simulation scenarios, yielding substantial increases in power to detect genomic regions associated with the simulated trait.Nos últimos anos muita atenção tem sido dada ao uso de polimorfismos de nucleotídeos simples (SNP para mapeamento fino do genoma, visando identificar mutações efetivas em características de interesse; todavia, muitos estudos focam apenas os efeitos marginais dos marcadores, ignorando as potenciais interações entre genes. Estudos de simulação tem mostrado que esta abordagem pode não ser poderosa o suficiente para detectar loci importantes quando interações entre genes estão presentes. Vários estudos tem examinado potenciais interações g

  11. Design of FIR Filters with Discrete Coefficients using Ant Colony Optimization

    Science.gov (United States)

    Tsutsumi, Shuntaro; Suyama, Kenji

    In this paper, we propose a new design method for linear phase FIR (Finite Impulse Response) filters with discrete coefficients. In a hardware implementation, filter coefficients must be represented as discrete values. The design problem of digital filters with discrete coefficients is formulated as the integer programming problem. Then, an enormous amount of computational time is required to solve the problem in a strict solver. Recently, ACO (Ant Colony Optimization) which is one heuristic approach, is used widely for solving combinational problem like the traveling salesman problem. In our method, we formulate the design problem as the 0-1 integer programming problem and solve it by using the ACO. Several design examples are shown to present effectiveness of the proposed method.

  12. Optimization of fuel reloads for a BWR using the ant colony system

    International Nuclear Information System (INIS)

    Esquivel E, J.; Ortiz S, J. J.

    2009-10-01

    In this work some results obtained during the development of optimization systems are presented, which are employees for the fuel reload design in a BWR. The systems use the ant colony optimization technique. As first instance, a system is developed that was adapted at travel salesman problem applied for the 32 state capitals of Mexican Republic. The purpose of this implementation is that a similarity exists with the design of fuel reload, since the two problems are of combinatorial optimization with decision variables that have similarity between both. The system was coupled to simulator SIMULATE-3, obtaining good results when being applied to an operation cycle in equilibrium for reactors of nuclear power plant of Laguna Verde. (Author)

  13. Reliability worth applied to transmission expansion planning based on ant colony system

    Energy Technology Data Exchange (ETDEWEB)

    Leite da Silva, Armando M.; Rezende, Leandro S. [Institute of Electric Systems and Energy, Federal University of Itajuba, UNIFEI (Brazil); da Fonseca Manso, Luiz A.; de Resende, Leonidas C. [Department of Electrical Engineering, Federal University of Sao Joao del Rei, UFSJ (Brazil)

    2010-12-15

    This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution, bearing in mind investment cost and reliability worth. Reliability worth is considered through the assessment of the interruption costs represented by the index LOLC - loss of load cost. The focus of this work is the development of a tool for the multi-stage planning of transmission systems and how reliability aspects can influence on the decision-making process. The applications of the proposed methodology are illustrated through case studies carried out using a test system and a real sub-transmission network. (author)

  14. Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems.

    Directory of Open Access Journals (Sweden)

    Zili Zhang

    Full Text Available Bi-objective Traveling Salesman Problem (bTSP is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM. PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs.

  15. Una aplicación de Ant Colony Optimization para la resolución de problemas de Flow Shop.

    OpenAIRE

    Bautista Valhondo, Joaquim; Companys Pascual, Ramón

    2001-01-01

    ACO, acrónimo de "Ant Colony Optimization", es una meta-heurística que puede emplearse en la resolución de problemas de optimización combinatoria; se inspira en el comportamiento de guía observado en las hormigas, y se caracteriza por la utilizac

  16. Hierarchical artificial bee colony algorithm for RFID network planning optimization.

    Science.gov (United States)

    Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

    2014-01-01

    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  17. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  18. Artificial bee colony algorithm with dynamic multi-population

    Science.gov (United States)

    Zhang, Ming; Ji, Zhicheng; Wang, Yan

    2017-07-01

    To improve the convergence rate and make a balance between the global search and local turning abilities, this paper proposes a decentralized form of artificial bee colony (ABC) algorithm with dynamic multi-populations by means of fuzzy C-means (FCM) clustering. Each subpopulation periodically enlarges with the same size during the search process, and the overlapping individuals among different subareas work for delivering information acting as exploring the search space with diffusion of solutions. Moreover, a Gaussian-based search equation with redefined local attractor is proposed to further accelerate the diffusion of the best solution and guide the search towards potential areas. Experimental results on a set of benchmarks demonstrate the competitive performance of our proposed approach.

  19. An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation

    International Nuclear Information System (INIS)

    Azadeh, A.; Skandari, M.R.; Maleki-Shoja, B.

    2010-01-01

    In this paper, an innovative model of agent based simulation, based on Ant Colony Optimization (ACO) algorithm is proposed in order to compare three available strategies of clearing wholesale electricity markets, i.e. uniform, pay-as-bid, and generalized Vickrey rules. The supply side actors of the power market are modeled as adaptive agents who learn how to bid strategically to optimize their profit through indirect interaction with other actors of the market. The proposed model is proper for bidding functions with high number of dimensions and enables modelers to avoid curse of dimensionality as dimension grows. Test systems are then used to study the behavior of each pricing rule under different degrees of competition and heterogeneity. Finally, the pricing rules are comprehensively compared using different economic criteria such as average cleared price, efficiency of allocation, and price volatility. Also, principle component analysis (PCA) is used to rank and select the best price rule. To the knowledge of the authors, this is the first study that uses ACO for assessing strategies of wholesale electricity market.

  20. Estimate of FDG Excretion by means of Compartmental Analysis and Ant Colony Optimization of Nuclear Medicine Data

    Science.gov (United States)

    Garbarino, Sara; Caviglia, Giacomo; Brignone, Massimo; Massollo, Michela; Sambuceti, Gianmario; Piana, Michele

    2013-01-01

    [18F]fluoro-2-deoxy-D-glucose (FDG) is one of the most utilized tracers for positron emission tomography (PET) applications in oncology. FDG-PET relies on higher glycolytic activity in tumors compared to normal structures as the basis of image contrast. As a glucose analog, FDG is transported into malignant cells which typically exhibit an increased radioactivity. However, different from glucose, FDG is not reabsorbed by the renal system and is excreted to the bladder. The present paper describes a novel computational method for the quantitative assessment of this excretion process. The method is based on a compartmental analysis of FDG-PET data in which the excretion process is explicitly accounted for by the bladder compartment and on the application of an ant colony optimization (ACO) algorithm for the determination of the tracer coefficients describing the FDG transport effectiveness. The validation of this approach is performed by means of both synthetic data and real measurements acquired by a PET device for small animals (micro-PET). Possible oncological applications of the results are discussed in the final section. PMID:24191175

  1. Bus Stops Location and Bus Route Planning Using Mean Shift Clustering and Ant Colony in West Jakarta

    Science.gov (United States)

    Supangat, Kenny; Eko Soelistio, Yustinus

    2017-03-01

    Traffic Jam has been a daily problem for people in Jakarta which is one of the busiest city in Indonesia up until now. Even though the official government has tried to reduce the impact of traffic issues by developing a new public transportation which takes up a lot of resources and time, it failed to diminish the problem. The actual concern to this problem actually lies in how people move between places in Jakarta where they always using their own vehicle like cars, and motorcycles that fill most of the street in Jakarta. Among much other public transportations that roams the street of Jakarta, Buses is believed to be an efficient transportation that can move many people at once. However, the location of the bus stop is now have moved to the middle of the main road, and its too far for the nearby residence to access to it. This paper proposes an optimal location of optimal bus stops in West Jakarta that is experimentally proven to have a maximal distance of 350 m. The optimal location is estimated by means of mean shift clustering method while the optimal routes are calculated using Ant Colony algorithm. The bus stops locations rate of error is 0.07% with overall route area of 32 km. Based on our experiments, we believe our proposed bus stop plan can be an interesting alternative to reduce traffic congestion in West Jakarta.

  2. Facilitating the 3D Indoor Search and Rescue Problem: An Overview of the Problem and an Ant Colony Solution Approach

    Science.gov (United States)

    Tashakkori, H.; Rajabifard, A.; Kalantari, M.

    2016-10-01

    Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.

  3. A queen pheromone induces workers to kill sexual larvae in colonies of the red imported fire ant (Solenopsis invicta).

    Science.gov (United States)

    Klobuchar, Emily A; Deslippe, Richard J

    2002-07-01

    We conducted five bioassays to study how queens control the execution of sexual larvae by workers in colonies of the red imported fire ant, Solenopsis invicta. In each assay, subset colonies were made from many large polygyne colonies, and the 20 sexual larvae they contained were monitored over time. Sexual larvae mostly survived in queenless colonies, but were mostly killed in colonies with a single dealated queen, regardless of whether or not the queen was fertilized. The larvae were also killed when fresh corpses of queens were added to queenless colonies. Whereas acetone extracts of queens did not produce a significant increase in killings, extracts in buffered saline induced workers to execute most sexual larvae, indicating successful extraction of an execution pheromone. We identified the probable storage location of the chemical as the poison sac, and found both fresh (1 day) and old (21 day) extracts of poison sacs to be equally effective in inducing executions. The pheromone is stable at room temperature, perhaps because venom alkaloids also present in the extracts keep the pheromone from degrading. It is apparently either proteinaceous or associated with a proteinaceous molecule, a novel finding, as no queen pheromone of a proteinaceous nature has been previously demonstrated in ants.

  4. Bee Colony Optimization - part I: The algorithm overview

    Directory of Open Access Journals (Sweden)

    Davidović Tatjana

    2015-01-01

    Full Text Available This paper is an extensive survey of the Bee Colony Optimization (BCO algorithm, proposed for the first time in 2001. BCO and its numerous variants belong to a class of nature-inspired meta-heuristic methods, based on the foraging habits of honeybees. Our main goal is to promote it among the wide operations research community. BCO is a simple, but efficient meta-heuristic technique that has been successfully applied to many optimization problems, mostly in transport, location and scheduling fields. Firstly, we shall give a brief overview of the other meta-heuristics inspired by bees’ foraging principles pointing out the differences between them. Then, we shall provide the detailed description of the BCO algorithm and its modifications, including the strategies for BCO parallelization, and giving the preliminary results regarding its convergence. The application survey is elaborated in Part II of our paper. [Projekat Ministarstva nauke Republike Srbije, br. OI174010, br. OI174033 i br. TR36002

  5. The interplay between maze complexity, colony size, learning and memory in ants while solving a maze: A test at the colony level.

    Science.gov (United States)

    Saar, Maya; Gilad, Tomer; Kilon-Kallner, Tal; Rosenfeld, Adar; Subach, Aziz; Scharf, Inon

    2017-01-01

    Central-place foragers need to explore their immediate habitat in order to reach food. We let colonies of the individually foraging desert ant Cataglyphis niger search for a food reward in a maze. We did so for three tests per day over two successive days and an additional test after a time interval of 4-20 days (seven tests in total). We examined whether the colonies reached the food reward faster, consumed more food and changed the number of workers searching over time, within and between days. Colonies' food-discovery time shortened within and between days, indicating that some workers learnt and became more efficient in moving through the maze. Such workers, however, also forgot and deteriorated in their food-discovery time, leveling off back to initial performance after about two weeks. We used mazes of increasing complexity levels, differing in the potential number of wrong turns. The number of workers searching increased with colony size. Food-discovery time also increased with colony size in complex mazes but not in simple ones, perhaps due to the more frequent interactions among workers in large colonies having to move through narrow routes. Finally, the motivation to solve the maze was probably not only the food reward, because food consumption did not change over time.

  6. A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains

    Science.gov (United States)

    Szemis, J. M.; Maier, H. R.; Dandy, G. C.

    2012-08-01

    Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.

  7. MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique.

    Science.gov (United States)

    Kumarasabapathy, N; Manoharan, P S

    2015-01-01

    This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC) for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs). The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion.

  8. MATLAB Simulation of UPQC for Power Quality Mitigation Using an Ant Colony Based Fuzzy Control Technique

    Directory of Open Access Journals (Sweden)

    N. Kumarasabapathy

    2015-01-01

    Full Text Available This paper proposes a fuzzy logic based new control scheme for the Unified Power Quality Conditioner (UPQC for minimizing the voltage sag and total harmonic distortion in the distribution system consequently to improve the power quality. UPQC is a recent power electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active power filters (APFs. The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality of the simplicity by tackling complex systems with vagueness and ambiguity. In this research, the fuzzy logic controller is utilized for the generation of reference signal controlling the UPQC. To enable this, a systematic approach for creating the fuzzy membership functions is carried out by using an ant colony optimization technique for optimal fuzzy logic control. An exhaustive simulation study using the MATLAB/Simulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logic controller and the simulation results are compared with the PI controller in terms of its performance in improving the power quality by minimizing the voltage sag and total harmonic distortion.

  9. Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

    Science.gov (United States)

    Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

    2018-02-01

    The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

  10. Graph Theory and ANT Colony Optimization Approach for Forest Patch Connectivity Analysis

    Science.gov (United States)

    Shantala Devi, B. S.; Murthy, M. S. R.; Pujar, G. S.; Debnath, B.

    2011-08-01

    Forest connectivity is necessary for prioritizing biodiversity conservation. Connectivity indices facilitate to predict the movement pattern of species across complex landscapes. Change in area and inter-patch distance in forest affects the biodiversity, wildlife movement, seed dispersal and other ecological factors. In graph theory components play an important role to analyze the group of patches and its impact with reference to the threshold distance between the patches. The study on link, threshold distance and components showed that with the increase in threshold distance, number of components decreased and number of links increased. Also Integral index of connectivity importance value (dIIC > 0.05) is high for big forest patches and considered to be intact forest. For those less than 0.05 importance value requires protection and conservation. Hence dIIC is categorised into Very low, low, Medium, high and Very high to analyze the degree of connectivity. Choosing correct threshold distance based on the requirement of species movement is preferred. Based on the selection of potential habitat patches shortest path between them is determined using Ant Colony Optimization (ACO) Technique. Vegetation type Map, Slope, Elevation, Disturbance Index, Biological Richness Map and DIIC layers facilitated to analyze the optimal path of the species through ACO for connectivity. Graph Theory and ACO works as a robust tool for Biodiversity Conservation.

  11. Offensive Strategy in the 2D Soccer Simulation League Using Multi-Group Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Shengbing Chen

    2016-02-01

    Full Text Available The 2D soccer simulation league is one of the best test beds for the research of artificial intelligence (AI. It has achieved great successes in the domain of multi-agent cooperation and machine learning. However, the problem of integral offensive strategy has not been solved because of the dynamic and unpredictable nature of the environment. In this paper, we present a novel offensive strategy based on multi-group ant colony optimization (MACO-OS. The strategy uses the pheromone evaporation mechanism to count the preference value of each attack action in different environments, and saves the values of success rate and preference in an attack information tree in the background. The decision module of the attacker then selects the best attack action according to the preference value. The MACO-OS approach has been successfully implemented in our 2D soccer simulation team in RoboCup competitions. The experimental results have indicated that the agents developed with this strategy, along with related techniques, delivered outstanding performances.

  12. Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

    Science.gov (United States)

    Li, Ke; Chen, Peng

    2011-01-01

    Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

  13. Colony Composition of Two Malaysian Ponerine Ants, Platythyrea Tricuspidata and P. Quadridenta: Sexual Reproduction by Workers and Production of Queens (Hymenoptera: Formicidae)

    OpenAIRE

    Ito, Fuminori

    1994-01-01

    Colonies of ponerine ants Platythyrea quadridenta and P. tricuspidata were collected in the rainforest of West Malaysia. Two colonies of P. tricuspidata were composed only of workers, and three and eight workers were inseminated per colony, respectively. However, active ovaries were found in one of the three, and two of the eight mated workers. P. quadridenta also exhibited sexual reproduction by workers, and there were many sterile mated workers. The two largest colonie...

  14. AN EFFICIENT APPROACH FOR DETECTION OF HEART ATTACK USING NOBLE ANT COLONY OPTIMIZATION CONCEPT OF DATA MINING

    OpenAIRE

    Pise Satish Prakashrao*1, Anoop Singh 2 & Ritesh Kumar Yadav3

    2018-01-01

    The goal of data mining is to extract knowledge from large amounts of data. Data Mining is an interdisciplinary field that focuses on machine learning, statistics and databases. In this article, we highlight a new framework that uses a combination of data extraction and ant colony optimization to collect heart disease such as early heart attacks to protect them and reduce mortality rates. This study focused on the formulation and implementation of an improved and reliable model for the diagno...

  15. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2007-09-21

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  16. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Vilches, M.; Lallena, A.M.

    2007-01-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool

  17. Social transmission of information about a mutualist via trophallaxis in ant colonies.

    Science.gov (United States)

    Hayashi, Masayuki; Hojo, Masaru K; Nomura, Masashi; Tsuji, Kazuki

    2017-08-30

    Partner discrimination is crucial in mutualistic interactions between organisms to counteract cheating by the partner. Trophobiosis between ants and aphids is a model system of such mutualistic interaction. To establish and maintain the mutualistic association, ants need to correctly discriminate mutualistic aphids. However, the mechanism by which ants recognize aphids as their partners is poorly understood, despite its ecological and evolutionary importance. Here, we show for the first time the evidence that interaction with nest-mates that have tended aphids ( Aphis craccivora ) allows ants ( Tetramorium tsushimae ) to learn to recognize the aphid species as their partner. When ants had previously tended aphids, they moderated their aggressiveness towards aphids. More importantly, ants that had interacted with aphid-experienced nest-mates also reduced their aggressiveness towards aphids, even though they had never directly experienced them, indicating that aphid information was transmitted from aphid-experienced ants to inexperienced ants. Furthermore, inhibition of mouth-to-mouth contact (trophallaxis) from aphid-experienced ants to inexperienced ants by providing the inexperienced ants with artificial honeydew solution caused the inexperienced ants to become aggressive towards aphids. These results, with further supporting data, strongly suggest that ants transfer information on their mutualists during trophallactic interactions. © 2017 The Author(s).

  18. Bacterial diversity in Solenopsis invicta and Solenopsis geminata ant colonies characterized by 16S amplicon 454 pyrosequencing.

    Science.gov (United States)

    Ishak, Heather D; Plowes, Rob; Sen, Ruchira; Kellner, Katrin; Meyer, Eli; Estrada, Dora A; Dowd, Scot E; Mueller, Ulrich G

    2011-05-01

    Social insects harbor diverse assemblages of bacterial microbes, which may play a crucial role in the success or failure of biological invasions. The invasive fire ant Solenopsis invicta (Formicidae, Hymenoptera) is a model system for understanding the dynamics of invasive social insects and their biological control. However, little is known about microbes as biotic factors influencing the success or failure of ant invasions. This pilot study is the first attempt to characterize and compare microbial communities associated with the introduced S. invicta and the native Solenopsis geminata in the USA. Using 16S amplicon 454 pyrosequencing, bacterial communities of workers, brood, and soil from nest walls were compared between neighboring S. invicta and S. geminata colonies at Brackenridge Field Laboratory, Austin, Texas, with the aim of identifying potential pathogenic, commensal, or mutualistic microbial associates. Two samples of S. geminata workers showed high counts of Spiroplasma bacteria, a known pathogen or mutualist of other insects. A subsequent analysis using PCR and sequencing confirmed the presence of Spiroplasma in additional colonies of both Solenopsis species. Wolbachia was found in one alate sample of S. geminata, while one brood sample of S. invicta had a high count of Lactococcus. As expected, ant samples from both species showed much lower microbial diversity than the surrounding soil. Both ant species had similar overall bacterial diversities, although little overlap in specific microbes. To properly characterize a single bacterial community associated with a Solenopsis ant sample, rarefaction analyses indicate that it is necessary to obtain 5,000-10,000 sequences. Overall, 16S amplicon 454 pyrosequencing appears to be a cost-effective approach to screen whole microbial diversity associated with invasive ant species.

  19. A hybrid expert system, clustering and ant colony optimization approach for scheduling and routing problem in courier services

    Directory of Open Access Journals (Sweden)

    Eduyn López-Santana

    2018-10-01

    Full Text Available This paper focuses on the problem of scheduling and routing workers in a courier service to deliver packages for a set of geographically distributed customers and, on a specific date and time window. The crew of workers has a limited capacity and a time window that represents their labor length. The problem deals with a combination of multiples variants of the vehicle routing problem as capacity, multiple periods, time windows, due dates and distance as constraints. Since in the courier services the demands could be of hundreds or thousands of packages to be delivered, the problem is computationally unmanageable. We present a three-phase solution approach. In the first phase, a scheduling model determines the visit date for each customer in the planning horizon by considering the release date, due date to visit and travel times. We use an expert system based on the know-how of the courier service, which uses an inference engine that works as a rule interpreter. In the second phase, a clustering model assigns, for each period, customers to workers according to the travel times, maximum load capacity and customer’s time windows. We use a centroid based and sweep algorithms to solve the resulted problem. Finally, in the third phase, a routing model finds the order in which each worker will visit all customers taking into account their time windows and worker’s available time. To solve the routing problem we use an Ant Colony Optimization metaheuristic. We present some numerical results using a case study, in which the proposed method of this paper finds better results in comparison with the current method used in the case study

  20. Application of the artificial bee colony algorithm for solving the set covering problem.

    Science.gov (United States)

    Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

    2014-01-01

    The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.

  1. Application of an Image Tracking Algorithm in Fire Ant Motion Experiment

    Directory of Open Access Journals (Sweden)

    Lichuan Gui

    2009-04-01

    Full Text Available An image tracking algorithm, which was originally used with the particle image velocimetry (PIV to determine velocities of buoyant solid particles in water, is modified and applied in the presented work to detect motion of fire ant on a planar surface. A group of fire ant workers are put to the bottom of a tub and excited with vibration of selected frequency and intensity. The moving fire ants are captured with an image system that successively acquires image frames of high digital resolution. The background noise in the imaging recordings is extracted by averaging hundreds of frames and removed from each frame. The individual fire ant images are identified with a recursive digital filter, and then they are tracked between frames according to the size, brightness, shape, and orientation angle of the ant image. The speed of an individual ant is determined with the displacement of its images and the time interval between frames. The trail of the individual fire ant is determined with the image tracking results, and a statistical analysis is conducted for all the fire ants in the group. The purpose of the experiment is to investigate the response of fire ants to the substrate vibration. Test results indicate that the fire ants move faster after being excited, but the number of active ones are not increased even after a strong excitation.

  2. Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

    Directory of Open Access Journals (Sweden)

    Morteza Atabati

    2016-09-01

    Full Text Available Quantitative structure–property relationship (QSPR studies based on ant colony optimization (ACO were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 descriptors. A major problem of QSPR is the high dimensionality of the descriptor space; therefore, descriptor selection is the most important step. In this paper, an ACO algorithm was used to select the best descriptors. Then selected descriptors were applied for model development using multiple linear regression. The average absolute relative deviation and correlation coefficient for the calibration set were obtained as 3.3% and 0.9591, respectively, while the average absolute relative deviation and correlation coefficient for the prediction set were obtained as 5.0% and 0.9526, respectively. The results showed that the applied procedure is suitable for prediction of λmax of 9,10-anthraquinone derivatives.

  3. ANT

    DEFF Research Database (Denmark)

    van der Duim, René; Ren, Carina Bregnholm; Jóhannesson, Gunnar Thór

    2017-01-01

    Ten years ago actor-network theory (ANT) entered this journal. To illustrate how the relational ontology and sensibilities of ANT lend themselves to particular kinds of research, we first interrogate the main controversies as a way to open up and discuss the main premises of ANT. These debates...... concern the status and agency of objects and non-humans, ANT’s denial of the explanatory power of social structures, and the political implications of ANT. Second we present ANT’s relevance for tourism studies and discuss what ANT ‘does’ in practice. After summarizing a decade of relations between ANT...... and tourism, we conclude by tracing three future trajectories of how we have ‘moved away with’ ANT into new areas of discovery....

  4. Emigration speed and the production of sexuals in colonies of the antTemnothorax crassispinusunder high and low levels of disturbance.

    Science.gov (United States)

    Mitrus, S

    A nest relocation is costly for social insects, and involves hazards. Emigrations were studied in Temnothorax crassispinus ant colonies, which inhabit ephemeral nest sites, and which frequently change their nests. In a laboratory experiment, ant colonies from one group were forced to change their nest sites 10 times over a ca. 3-month period, whilst colonies from the second group were forced to adopt this practice twice (on the beginning of May, and in the second half of July). Colonies of the ant from both the groups reduced their total emigration duration. However, the duration of the transport phase remained unchanged. In the case of colonies with higher level of disturbance, there was no relation between colony growth rate and energy allocation in sexual individuals, whilst a negative correlation between these parameters was present in group with lower level of disturbance. In colonies with lower level of disturbance, the investment in sexuals was not correlated with the number of workers at the end of the experiment, whereas such a correlation was demonstrated for colonies with higher level of disturbance. The disturbance, and thus necessity of frequent nest relocations, may be perceived by ants as a signal that nest sites are of a lower quality and may contribute to a change in energy allocation.

  5. Threshold based AntNet algorithm for dynamic traffic routing of road networks

    Directory of Open Access Journals (Sweden)

    Ayman M. Ghazy

    2012-07-01

    Full Text Available Dynamic routing algorithms play an important role in road traffic routing to avoid congestion and to direct vehicles to better routes. AntNet routing algorithms have been applied, extensively and successfully, in data communication network. However, its application for dynamic routing on road networks is still considerably limited. This paper presents a modified version of the AntNet routing algorithm, called “Threshold based AntNet”, that has the ability to efficiently utilize a priori information of dynamic traffic routing, especially, for road networks. The modification exploits the practical and pre-known information for most road traffic networks, namely, the good travel times between sources and destinations. The values of those good travel times are manipulated as threshold values. This approach has proven to conserve tracking of good routes. According to the dynamic nature of the problem, the presented approach guards the agility of rediscovering a good route. Attaining the thresholds (good reported travel times, of a given source to destination route, permits for a better utilization of the computational resources, that, leads to better accommodation for the network changes. The presented algorithm introduces a new type of ants called “check ants”. It assists in preserving good routes and, better yet, exposes and discards the degraded ones. The threshold AntNet algorithm presents a new strategy for updating the routing information, supported by the backward ants.

  6. Scaling of differentiation in networks: nervous systems, organisms, ant colonies, ecosystems, businesses, universities, cities, electronic circuits, and Legos.

    Science.gov (United States)

    Changizi, M A; McDannald, M A; Widders, D

    2002-09-21

    Nodes in networks are often of different types, and in this sense networks are differentiated. Here we examine the relationship between network differentiation and network size in networks under economic or natural selective pressure, such as electronic circuits (networks of electronic components), Legos (networks of Lego pieces), businesses (networks of employees), universities (networks of faculty), organisms (networks of cells), ant colonies (networks of ants), and nervous systems (networks of neurons). For each of these we find that (i) differentiation increases with network size, and (ii) the relationship is consistent with a power law. These results are explained by a hypothesis that, because nodes are costly to build and maintain in such "selected networks", network size is optimized, and from this the power-law relationship may be derived. The scaling exponent depends on the particular kind of network, and is determined by the degree to which nodes are used in a combinatorial fashion to carry out network-level functions. We find that networks under natural selection (organisms, ant colonies, and nervous systems) have much higher combinatorial abilities than the networks for which human ingenuity is involved (electronic circuits, Legos, businesses, and universities). A distinct but related optimization hypothesis may be used to explain scaling of differentiation in competitive networks (networks where the nodes themselves, rather than the entire network, are under selective pressure) such as ecosystems (networks of organisms).

  7. Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem

    OpenAIRE

    Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando

    2014-01-01

    The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show...

  8. The effect of symbiotic ant colonies on plant growth: a test using an Azteca-Cecropia system.

    Directory of Open Access Journals (Sweden)

    Karla N Oliveira

    Full Text Available In studies of ant-plant mutualisms, the role that ants play in increasing the growth rates of their plant partners is potentially a key beneficial service. In the field, we measured the growth of Cecropia glaziovii saplings and compared individuals that were naturally colonized by Azteca muelleri ants with uncolonized plants in different seasons (wet and dry. We also measured light availability as well as attributes that could be influenced by the presence of Azteca colonies, such as herbivory, leaf nutrients (total nitrogen and δ(15N, and investments in defense (total phenolics and leaf mass per area. We found that colonized plants grew faster than uncolonized plants and experienced a lower level of herbivory in both the wet and dry seasons. Colonized plants had higher nitrogen content than uncolonized plants, although the δ(15N, light environment, total phenolics and leaf mass per area, did not differ between colonized and uncolonized plants. Since colonized and uncolonized plants did not differ in the direct defenses that we evaluated, yet herbivory was lower in colonized plants, we conclude that biotic defenses were the most effective protection against herbivores in our system. This result supports the hypothesis that protection provided by ants is an important factor promoting plant growth. Since C. glaziovii is widely distributed among a variety of forests and ecotones, and since we demonstrated a strong relationship with their ant partners, this system can be useful for comparative studies of ant-plant interactions in different habitats. Also, given this study was carried out near the transition to the subtropics, these results help generalize the geographic distribution of this mutualism and may shed light on the persistence of the interactions in the face of climate change.

  9. Autonomously Implemented Versatile Path Planning for Mobile Robots Based on Cellular Automata and Ant Colony

    Directory of Open Access Journals (Sweden)

    Adel Akbarimajd

    2012-02-01

    Full Text Available A path planning method for mobile robots based on two dimensional cellular automata is proposed. The method can be applied for environments with both concave and convex obstacles. It is also appropriate for multi-robot problems as well as dynamic environments. In order to develop the planning method, environment of the robot is decomposed to a rectangular grid and the automata is defined with four states including Robot cell, Free cell, Goal cell and Obstacle cell. Evolution rules of automata are proposed in order to direct the robot toward its goal. CA based path planner method is afterwards modified by a colony technique to be applicable for concave obstacles. Then a layered architecture is proposed to autonomously implement the planning algorithm. The architecture employs an abstraction approach which makes the complexity manageable. An important feature of the architecture is internal artifacts that have some beliefs about the world. Most actions of the robot are planned and performed with respect to these artifacts.

  10. Ocurrence of the antibiotic producing bacterium Burkholderia sp. in colonies of the leaf-cutting ant Atta sexdens rubropilosa.

    Science.gov (United States)

    Santos, Adão Valmir; Dillon, Rod J; Dillon, Viv M; Reynolds, Stuart E; Samuels, Richard I

    2004-10-15

    Fungus garden material from recently established Atta sexdens rubropilosa colonies (6-12 months old) was sampled to detect antibiotic producing microorganisms that inhibited the growth of pathogens of insects and of the fungus gardens but did not affect their mutualistic fungus. A bacterium with activity against the entomopathogenic fungus Beauveria bassiana was isolated from 56% of the gardens tested (n=57) and identified from its biochemical profile and from 16S and 23S ribosomal DNA sequences as a member of the genus Burkholderia. The ant-associated Burkholderia isolates secreted a potent, anti-fungal agent that inhibited germination of conidia of the entomopathogenic fungi B. bassiana, Metarhizium anisopliae, of the saprophytic Verticillium lecanii, and also of a specialist fungus garden Escovopsis weberi. Growth of the ant's mutualist fungus was unaffected.

  11. CodeRAnts: A recommendation method based on collaborative searching and ant colonies, applied to reusing of open source code

    Directory of Open Access Journals (Sweden)

    Isaac Caicedo-Castro

    2014-01-01

    Full Text Available This paper presents CodeRAnts, a new recommendation method based on a collaborative searching technique and inspired on the ant colony metaphor. This method aims to fill the gap in the current state of the matter regarding recommender systems for software reuse, for which prior works present two problems. The first is that, recommender systems based on these works cannot learn from the collaboration of programmers and second, outcomes of assessments carried out on these systems present low precision measures and recall and in some of these systems, these metrics have not been evaluated. The work presented in this paper contributes a recommendation method, which solves these problems.

  12. Optimising social information by game theory and ant colony method to enhance routing protocol in opportunistic networks

    Directory of Open Access Journals (Sweden)

    Chander Prabha

    2016-09-01

    Full Text Available The data loss and disconnection of nodes are frequent in the opportunistic networks. The social information plays an important role in reducing the data loss because it depends on the connectivity of nodes. The appropriate selection of next hop based on social information is critical for improving the performance of routing in opportunistic networks. The frequent disconnection problem is overcome by optimising the social information with Ant Colony Optimization method which depends on the topology of opportunistic network. The proposed protocol is examined thoroughly via analysis and simulation in order to assess their performance in comparison with other social based routing protocols in opportunistic network under various parameters settings.

  13. A methodology for obtaining the control rods patterns in a BWR using systems based on ants colonies

    International Nuclear Information System (INIS)

    Ortiz S, J.J.; Requena R, I.

    2003-01-01

    In this work the AZCATL-PBC system based on a technique of ants colonies for the search of control rods patterns of those reactors of the Nuclear Power station of Laguna Verde (CNLV) is presented. The technique was applied to a transition cycle and one of balance. For both cycles they were compared the k ef values obtained with a Haling calculation and the control rods pattern proposed by AZCATL-PBC for a burnt one fixed. It was found that the methodology is able to extend the length of the cycle with respect to the Haling prediction, maintaining sure to the reactor. (Author)

  14. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. A General Combinatorial Ant System-based Distributed Routing Algorithm for Communication Networks

    Directory of Open Access Journals (Sweden)

    Jose Aguilar

    2007-08-01

    Full Text Available In this paper, a general Combinatorial Ant System-based distributed routing algorithm modeled like a dynamic combinatorial optimization problem is presented. In the proposed algorithm, the solution space of the dynamic combinatorial optimization problem is mapped into the space where the ants will walk, and the transition probability and the pheromone update formula of the Ant System is defined according to the objective function of the communication problem. The general nature of the approach allows for the optimization of the routing function to be applied in different types of networks just changing the performance criteria to be optimized. In fact, we test and compare the performance of our routing algorithm against well-known routing schemes for wired and wireless networks, and show its superior performance in terms throughput, delay and energy efficiency.

  16. ADAPTIVE CLUSTER BASED ROUTING PROTOCOL WITH ANT COLONY OPTIMIZATION FOR MOBILE AD-HOC NETWORK IN DISASTER AREA

    Directory of Open Access Journals (Sweden)

    Enrico Budianto

    2012-07-01

    Full Text Available In post-disaster rehabilitation efforts, the availability of telecommunication facilities takes important role. However, the process to improve telecommunication facilities in disaster area is risky if it is done by humans. Therefore, a network method that can work efficiently, effectively, and capable to reach the widest possible area is needed. This research introduces a cluster-based routing protocol named Adaptive Cluster Based Routing Protocol (ACBRP equipped by Ant Colony Optimization method, and its implementation in a simulator developed by author. After data analysis and statistical tests, it can be concluded that routing protocol ACBRP performs better than AODV and DSR routing protocol. Pada upaya rehabilitasi pascabencana, ketersediaan fasilitas telekomunikasi memiliki peranan yang sangat penting. Namun, proses untuk memperbaiki fasilitas telekomunikasi di daerah bencana memiliki resiko jika dilakukan oleh manusia. Oleh karena itu, metode jaringan yang dapat bekerja secara efisien, efektif, dan mampu mencapai area seluas mungkin diperlukan. Penelitian ini memperkenalkan sebuah protokol routing berbasis klaster bernama Adaptive Cluster Based Routing Protocol (ACBRP, yang dilengkapi dengan metode Ant Colony Optimization, dan diimplementasikan pada simulator yang dikembangkan penulis. Setelah data dianalisis dan dilakukan uji statistik, disimpulkan bahwa protokol routing ACBRP beroperasi lebih baik daripada protokol routing AODV maupun DSR.

  17. Colony Diet Influences Ant Worker Foraging and Attendance of Myrmecophilous Lycaenid Caterpillars

    Directory of Open Access Journals (Sweden)

    Sebastian Pohl

    2016-09-01

    Full Text Available Foraging animals regulate their intake of macronutrients such as carbohydrates and proteins. However, regulating the intake of these two macronutrients can be constrained by the nutrient content of available food sources. Compensatory foraging is a method to adjust nutrient intake under restricted nutrient availability by preferentially exploiting food sources that contain limiting nutrients. Here we studied the potential for compensatory foraging in the dolichoderine ant Iridomyrmex mayri, which is commonly found in associations with caterpillars of the obligatorily ant-associated lycaenid butterfly Jalmenus evagoras. The caterpillars receive protection against predators and parasites, and reward the ants with nutritional secretions from specialized exocrine glands. These secretions contain a mixture of sugars and free amino acids, particularly serine. We tested the influence of nutrient-deficient diets on foraging patterns in I. mayri by recording the intake of test solutions containing single types of macronutrients during food preference tests. We also investigated the level of ant attendance on fifth instar J. evagoras caterpillars to evaluate how changes in diet influenced ant tending of caterpillars and foraging on their secretions. Foragers on a protein diet compensated for the nutritional deficit by increasing the intake of test solutions that contained sucrose, compared to their counterparts on a non-restricted diet. Ants on a sugar diet, however, did not show a corresponding increased consumption of test solutions containing the amino acid serine. Additionally, compared with their counterparts on a mixed diet, ants on limited nutrient diets showed an increase in the number of caterpillar-tending workers, suggesting that the caterpillars’ secretions are suitable to compensate for the ants’ nutritional deficit.

  18. Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2014-01-01

    Full Text Available The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms.

  19. Automatic optimization of a nuclear reactor reload using the algorithm Ant-Q; A otimizacao automatica da recarga nuclear utilizando o algoritmo Ant-Q

    Energy Technology Data Exchange (ETDEWEB)

    Machado, Liana; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear

    2002-07-01

    The nuclear fuel reload optimization is a NP-Complete combinatorial optimization problem. For decades this problem was solved using an expert's knowledge. From the eighties, however there have been efforts to automatic fuel reload and the more recent ones show the Genetic Algorithm's (GA) efficiency on this problem. Following this trend, our aim is to optimization nuclear fuel reload using Ant-Q, artificial theory based algorithms. Ant-Q's results on the Traveling salesman Problem, which is conceptuality similar to fuel reload, are better than GA's. Ant-Q was tested in real application on the cycle 7 reload of Angra I. Comparing Ant-Q result with the GA's, it can be verified that, even without a local heuristics, the former algorithm, as it superiority comparing the GA in Angra I show. Is a valid technique to solve the nuclear fuel reload problem. (author)

  20. A novel hybrid chaotic ant swarm algorithm for heat exchanger networks synthesis

    International Nuclear Information System (INIS)

    Zhang, Chunwei; Cui, Guomin; Peng, Fuyu

    2016-01-01

    Highlights: • The chaotic ant swarm algorithm is proposed to avoid trapping into a local optimum. • The organization variables update strategy makes full use of advantages of the chaotic search. • The structure evolution strategy is developed to handle integer variables optimization. • Overall three cases taken form the literatures are investigated with better optima. - Abstract: The heat exchanger networks synthesis (HENS) still remains an open problem due to its combinatorial nature, which can easily result in suboptimal design and unacceptable calculation effort. In this paper, a novel hybrid chaotic ant swarm algorithm is proposed. The presented algorithm, which consists of a combination of chaotic ant swarm (CAS) algorithm, structure evolution strategy, local optimization strategy and organization variables update strategy, can simultaneously optimize continuous variables and integer variables. The CAS algorithm chaotically searches and generates new solutions in the given space, and subsequently the structure evolution strategy evolves the structures represented by the solutions and limits the search space. Furthermore, the local optimizing strategy and the organization variables update strategy are introduced to enhance the performance of the algorithm. The study of three different cases, found in the literature, revealed special search abilities in both structure space and continuous variable space.

  1. Development of Hybrid Model for Estimating Construction Waste for Multifamily Residential Buildings Using Artificial Neural Networks and Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Dongoun Lee

    2016-09-01

    Full Text Available Due to the increasing costs of construction waste disposal, an accurate estimation of the amount of construction waste is a key factor in a project’s success. Korea has been burdened by increasing construction waste as a consequence of the growing number of construction projects and a lack of construction waste management (CWM strategies. One of the problems associated with predicting the amount of waste is that there are no suitable estimation strategies currently available. Therefore, we developed a hybrid estimation model to predict the quantity and cost of waste in the early stage of construction. The proposed approach can be used to address cost overruns and improve CWM in the subsequent stages of construction. The proposed hybrid model uses artificial neural networks (ANNs and ant colony optimization (ACO. It is expected to provide an accurate waste estimate by applying historical data from multifamily residential buildings.

  2. Dynamic population artificial bee colony algorithm for multi-objective optimal power flow

    Directory of Open Access Journals (Sweden)

    Man Ding

    2017-03-01

    Full Text Available This paper proposes a novel artificial bee colony algorithm with dynamic population (ABC-DP, which synergizes the idea of extended life-cycle evolving model to balance the exploration and exploitation tradeoff. The proposed ABC-DP is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. ABC-DP is then used for solving the optimal power flow (OPF problem in power systems that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results, which are also compared to nondominated sorting genetic algorithm II (NSGAII and multi-objective ABC (MOABC, are presented to illustrate the effectiveness and robustness of the proposed method.

  3. Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization

    Directory of Open Access Journals (Sweden)

    Li Mao

    2016-01-01

    Full Text Available Artificial bee colony (ABC algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum. In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC algorithm. To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages. Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms.

  4. A Modified Artificial Bee Colony Algorithm for p-Center Problems

    Directory of Open Access Journals (Sweden)

    Alkın Yurtkuran

    2014-01-01

    Full Text Available The objective of the p-center problem is to locate p-centers on a network such that the maximum of the distances from each node to its nearest center is minimized. The artificial bee colony algorithm is a swarm-based meta-heuristic algorithm that mimics the foraging behavior of honey bee colonies. This study proposes a modified ABC algorithm that benefits from a variety of search strategies to balance exploration and exploitation. Moreover, random key-based coding schemes are used to solve the p-center problem effectively. The proposed algorithm is compared to state-of-the-art techniques using different benchmark problems, and computational results reveal that the proposed approach is very efficient.

  5. A new improved artificial bee colony algorithm for ship hull form optimization

    Science.gov (United States)

    Huang, Fuxin; Wang, Lijue; Yang, Chi

    2016-04-01

    The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

  6. Penerapan Bee Colony Optimization Algorithm untuk Penentuan Rute Terpendek (Studi Kasus : Objek Wisata Daerah Istimewa Yogyakarta

    Directory of Open Access Journals (Sweden)

    Danuri Danuri

    2013-01-01

    Abstract The shortest path determination is an optimization problem which often used as a case study for research. Distance is the most defining factor in performing the search paths to be passed. Path with the shortest distance would be chosen as a path selection. Bee colony optimization algorithm used in this study to complete problems shortest path determination. There are two main process es during search path that is forward and backward. Bee colony optimization algorithm works on the process forward. The value probability of a path is base intransition process and the duration of waggle dance track of every bee who had found the position of the goal will be a preferred route. The results obtained in this study is the bee colony optimization algorithm can be used to find shortest path. The number of bees are released greatly affects in finding routes that can be passed. The more the number of bees that removed the greater the chances of finding the shortest path.   Keyword— Shortest Path, Bee Colony Optimization Algorithm

  7. Ant Colony Optimization Approaches to Clustering of Lung Nodules from CT Images

    Directory of Open Access Journals (Sweden)

    Ravichandran C. Gopalakrishnan

    2014-01-01

    Full Text Available Lung cancer is becoming a threat to mankind. Applying machine learning algorithms for detection and segmentation of irregular shaped lung nodules remains a remarkable milestone in CT scan image analysis research. In this paper, we apply ACO algorithm for lung nodule detection. We have compared the performance against three other algorithms, namely, Otsu algorithm, watershed algorithm, and global region based segmentation. In addition, we suggest a novel approach which involves variations of ACO, namely, refined ACO, logical ACO, and variant ACO. Variant ACO shows better reduction in false positives. In addition we propose black circular neighborhood approach to detect nodule centers from the edge detected image. Genetic algorithm based clustering is performed to cluster the nodules based on intensity, shape, and size. The performance of the overall approach is compared with hierarchical clustering to establish the improvisation in the proposed approach.

  8. Colony Structure and Nest Location of Two Species of Dacetine Ants: Pyramica ohioensis (Kennedy & Schramm and Pyramica rostrata (Emery in Maryland (Hymenoptera: Formicidae

    Directory of Open Access Journals (Sweden)

    Richard M. Duffield

    2011-01-01

    Full Text Available The discovery of numerous Pyramica ohioensis and P. rostrata colonies living in acorns, as well as the efficient recovery of colonies from artificial nests placed in suitable habitats, opens a new stage in the study of North American dacetine ants. Here we present detailed information, based on 42 nest collections, on the colony structure of these two species. P. ohioensis colonies are smaller than those of P. rostrata. Both species are polygynous, but nests of P. ohioensis contain fewer dealate queens than those of P. rostrata. This is the first report of multiple collections of Pyramica colonies nesting in fallen acorns, and of the use of artificial nesting cavities to sample for dacetines in the soil and leaf litter. We describe an artificial cavity nest design that may prove useful in future investigations.

  9. Hybrid Artificial Bee Colony Algorithm and Particle Swarm Search for Global Optimization

    Directory of Open Access Journals (Sweden)

    Wang Chun-Feng

    2014-01-01

    Full Text Available Artificial bee colony (ABC algorithm is one of the most recent swarm intelligence based algorithms, which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To overcome this problem, we propose a novel artificial bee colony algorithm based on particle swarm search mechanism. In this algorithm, for improving the convergence speed, the initial population is generated by using good point set theory rather than random selection firstly. Secondly, in order to enhance the exploitation ability, the employed bee, onlookers, and scouts utilize the mechanism of PSO to search new candidate solutions. Finally, for further improving the searching ability, the chaotic search operator is adopted in the best solution of the current iteration. Our algorithm is tested on some well-known benchmark functions and compared with other algorithms. Results show that our algorithm has good performance.

  10. A Multiuser Detector Based on Artificial Bee Colony Algorithm for DS-UWB Systems

    Directory of Open Access Journals (Sweden)

    Zhendong Yin

    2013-01-01

    Full Text Available Artificial Bee Colony (ABC algorithm is an optimization algorithm based on the intelligent behavior of honey bee swarm. The ABC algorithm was developed to solve optimizing numerical problems and revealed premising results in processing time and solution quality. In ABC, a colony of artificial bees search for rich artificial food sources; the optimizing numerical problems are converted to the problem of finding the best parameter which minimizes an objective function. Then, the artificial bees randomly discover a population of initial solutions and then iteratively improve them by employing the behavior: moving towards better solutions by means of a neighbor search mechanism while abandoning poor solutions. In this paper, an efficient multiuser detector based on a suboptimal code mapping multiuser detector and artificial bee colony algorithm (SCM-ABC-MUD is proposed and implemented in direct-sequence ultra-wideband (DS-UWB systems under the additive white Gaussian noise (AWGN channel. The simulation results demonstrate that the BER and the near-far effect resistance performances of this proposed algorithm are quite close to those of the optimum multiuser detector (OMD while its computational complexity is much lower than that of OMD. Furthermore, the BER performance of SCM-ABC-MUD is not sensitive to the number of active users and can obtain a large system capacity.

  11. Optimization of type-2 fuzzy controllers using the bee colony algorithm

    CERN Document Server

    Amador, Leticia

    2017-01-01

    This book focuses on the fields of fuzzy logic, bio-inspired algorithm; especially bee colony optimization algorithm and also considering the fuzzy control area. The main idea is that this areas together can to solve various control problems and to find better results. In this book we test the proposed method using two benchmark problems; the problem for filling a water tank and the problem for controlling the trajectory in an autonomous mobile robot. When Interval Type-2 Fuzzy Logic System is implemented to model the behavior of systems, the results show a better stabilization, because the analysis of uncertainty is better. For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.

  12. Double evolutsional artificial bee colony algorithm for multiple traveling salesman problem

    Directory of Open Access Journals (Sweden)

    Xue Ming Hao

    2016-01-01

    Full Text Available The double evolutional artificial bee colony algorithm (DEABC is proposed for solving the single depot multiple traveling salesman problem (MTSP. The proposed DEABC algorithm, which takes advantage of the strength of the upgraded operators, is characterized by its guidance in exploitation search and diversity in exploration search. The double evolutional process for exploitation search is composed of two phases of half stochastic optimal search, and the diversity generating operator for exploration search is used for solutions which cannot be improved after limited times. The computational results demonstrated the superiority of our algorithm over previous state-of-the-art methods.

  13. Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Weiqiang Dong

    2016-09-01

    Full Text Available A distributed power system with renewable energy sources is very popular in recent years due to the rapid depletion of conventional sources of energy. Reasonable sizing for such power systems could improve the power supply reliability and reduce the annual system cost. The goal of this work is to optimize the size of a stand-alone hybrid photovoltaic (PV/wind turbine (WT/battery (B/hydrogen system (a hybrid system based on battery and hydrogen (HS-BH for reliable and economic supply. Two objectives that take the minimum annual system cost and maximum system reliability described as the loss of power supply probability (LPSP have been addressed for sizing HS-BH from a more comprehensive perspective, considering the basic demand of load, the profit from hydrogen, which is produced by HS-BH, and an effective energy storage strategy. An improved ant colony optimization (ACO algorithm has been presented to solve the sizing problem of HS-BH. Finally, a simulation experiment has been done to demonstrate the developed results, in which some comparisons have been done to emphasize the advantage of HS-BH with the aid of data from an island of Zhejiang, China.

  14. Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

    Science.gov (United States)

    Cao, Lu; Chen, Qiwei

    2018-03-01

    Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

  15. Using an Improved Artificial Bee Colony Algorithm for Parameter Estimation of a Dynamic Grain Flow Model

    Directory of Open Access Journals (Sweden)

    He Wang

    2018-01-01

    Full Text Available An effective method is proposed to estimate the parameters of a dynamic grain flow model (DGFM. To this end, an improved artificial bee colony (IABC algorithm is used to estimate unknown parameters of DGFM with minimizing a given objective function. A comparative study of the performance of the IABC algorithm and the other ABC variants on several benchmark functions is carried out, and the results present a significant improvement in performance over the other ABC variants. The practical application performance of the IABC is compared to that of the nonlinear least squares (NLS, particle swarm optimization (PSO, and genetic algorithm (GA. The compared results demonstrate that IABC algorithm is more accurate and effective for the parameter estimation of DGFM than the other algorithms.

  16. Coming of age in an ant colony: cephalic muscle maturation accompanies behavioral development in Pheidole dentata

    Science.gov (United States)

    Muscedere, Mario L.; Traniello, James F. A.; Gronenberg, Wulfila

    2011-09-01

    Although several neurobiological and genetic correlates of aging and behavioral development have been identified in social insect workers, little is known about how other age-related physiological processes, such as muscle maturation, contribute to task performance. We examined post-eclosion growth of three major muscles of the head capsule in major and minor workers of the ant Pheidole dentata using workers of different ages with distinct task repertoires. Mandible closer muscle fibers, which provide bite force and are thus critical for the use of the mandibles for biting and load carrying, fill the posterio-lateral portions of the head capsule in mature, older workers of both subcastes. Mandible closer fibers of newly eclosed workers, in contrast, are significantly thinner in both subcastes and grow during at least the next 6 days in minor workers, suggesting this muscle has reduced functionality for a substantial period of adult life and thus constrains task performance capability. Fibers of the antennal muscles and the pharynx dilator, which control antennal movements and food intake, respectively, also increase significantly in thickness with age. However, these fibers are only slightly thinner in newly eclosed workers and attain their maximum thickness over a shorter time span in minors. The different growth rates of these functionally distinct muscles likely have consequences for how adult P. dentata workers, particularly minors, develop their full and diverse task repertoire as they age. Workers may be capable of feeding and interacting socially soon after eclosion, but require a longer period of development to effectively use their mandibles, which enable the efficient performance of tasks ranging from nursing to foraging and defense.

  17. Novel PID Tracking Controller for 2DOF Robotic Manipulator System Based on Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Elkhateeb Nasr A.

    2017-12-01

    Full Text Available This study presents a well-developed optimization methodology based on the dynamic inertia weight Artificial Bee Colony algorithm (ABC to design an optimal PID controller for a robotic arm manipulator. The dynamical analysis of robotic arm manipulators investigates a coupling relation between the joint torques applied by the actuators and the position and acceleration of the robot arm. An optimal PID control law is obtained from the proposed (ABC algorithm and applied to the robotic system. The designed controller optimizes the trajectory of the robot’s end effector for a time-variant input and makes the robot robust in the presence of external disturbance.

  18. A Modified Artificial Bee Colony Algorithm Application for Economic Environmental Dispatch

    Science.gov (United States)

    Tarafdar Hagh, M.; Baghban Orandi, Omid

    2018-03-01

    In conventional fossil-fuel power systems, the economic environmental dispatch (EED) problem is a major problem that optimally determines the output power of generating units in a way that cost of total production and emission level be minimized simultaneously, and at the same time all the constraints of units and system are satisfied properly. To solve EED problem which is a non-convex optimization problem, a modified artificial bee colony (MABC) algorithm is proposed in this paper. This algorithm by implementing weighted sum method is applied on two test systems, and eventually, obtained results are compared with other reported results. Comparison of results confirms superiority and efficiency of proposed method clearly.

  19. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps

    Science.gov (United States)

    Mao, Wei; Li, Hao-ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions. PMID:27293426

  20. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps.

    Science.gov (United States)

    Mao, Wei; Lan, Heng-You; Li, Hao-Ru

    2016-01-01

    As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D = 20 and D = 40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions.

  1. A New Modified Artificial Bee Colony Algorithm with Exponential Function Adaptive Steps

    Directory of Open Access Journals (Sweden)

    Wei Mao

    2016-01-01

    Full Text Available As one of the most recent popular swarm intelligence techniques, artificial bee colony algorithm is poor at exploitation and has some defects such as slow search speed, poor population diversity, the stagnation in the working process, and being trapped into the local optimal solution. The purpose of this paper is to develop a new modified artificial bee colony algorithm in view of the initial population structure, subpopulation groups, step updating, and population elimination. Further, depending on opposition-based learning theory and the new modified algorithms, an improved S-type grouping method is proposed and the original way of roulette wheel selection is substituted through sensitivity-pheromone way. Then, an adaptive step with exponential functions is designed for replacing the original random step. Finally, based on the new test function versions CEC13, six benchmark functions with the dimensions D=20 and D=40 are chosen and applied in the experiments for analyzing and comparing the iteration speed and accuracy of the new modified algorithms. The experimental results show that the new modified algorithm has faster and more stable searching and can quickly increase poor population diversity and bring out the global optimal solutions.

  2. An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators

    Directory of Open Access Journals (Sweden)

    Jiuyuan Huo

    2017-02-01

    Full Text Available To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC inspired by the intelligent foraging behavior of honey bees was proposed in this paper. The proposed algorithm utilizes the Pareto dominance theory and takes advantage of adaptive grid and regulation operator mechanisms. The adaptive grid technique is used to adaptively assess the Pareto front maintained in an external archive and the regulation operator is used to balance the weights of the local search and the global search in the evolution of the algorithm. The performance of RMOABC was evaluated in comparison with other nature inspired algorithms includes NSGA-II and MOEA/D. The experiments results demonstrated that the RMOABC approach has better accuracy and minimal execution time.

  3. A nuclear reactor core fuel reload optimization using Artificial-Ant-Colony Connective Networks; Recarga de reatores nucleares utilizando redes conectivas de colonias de formigas artificiais

    Energy Technology Data Exchange (ETDEWEB)

    Lima, Alan M.M. de; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]. E-mail: alan@lmp.ufrj.br; schirru@lmp.ufrj.br

    2005-07-01

    A Pressurized Water Reactor core must be reloaded every time the fuel burnup reaches a level when it is not possible to sustain nominal power operation. The nuclear core fuel reload optimization consists in finding a burned-up and fresh-fuel-assembly pattern that maximizes the number of full operational days. This problem is NP-hard, meaning that complexity grows exponentially with the number of fuel assemblies in the core. Besides that, the problem is non-linear and its search space is highly discontinual and multimodal. In this work a parallel computational system based on Ant Colony System (ACS) called Artificial-Ant-Colony Networks is introduced to solve the nuclear reactor core fuel reload optimization problem. ACS is a system based on artificial agents that uses the reinforcement learning technique and was originally developed to solve the Traveling Salesman Problem, which is conceptually similar to the nuclear fuel reload problem. (author)

  4. Identifying nuclear power plant transients using the Discrete Binary Artificial Bee Colony (DBABC) algorithm

    International Nuclear Information System (INIS)

    Oliveira, Iona M.S. de; Schirru, Roberto

    2011-01-01

    The identification of possible transients in a nuclear power plant is a highly relevant problem. This is mainly due to the fact that the operation of a nuclear power plant involves a large number of state variables whose behaviors are extremely dynamic. In risk situations, besides the huge cognitive overload that operators are submitted to, there is also the problem related with the considerable decrease in the effective time for correct decision making. To minimize these problems and help operators to make the corrective actions in due time, this paper presents a new contribution in this area and introduces an experimental transient identification system based exclusively on the abilities of the Discrete Binary Artificial Bee Colony (DBABC) algorithm to find the best centroid positions that correctly identifies a transient in a nuclear power plant. The DBABC is a reworking of the Artificial Bee Colony (ABC) algorithm which presents the advantage of operating in both continuous and discrete search spaces. Through the analysis of experimental results, the effective performance of the proposed DBABC algorithm is shown against some well known best performing algorithms from the literature. (author)

  5. Propagule pressure and colony social organization are associated with the successful invasion and rapid range expansion of fire ants in China.

    Science.gov (United States)

    Yang, Chin-Cheng; Ascunce, Marina S; Luo, Li-Zhi; Shao, Jing-Guo; Shih, Cheng-Jen; Shoemaker, DeWayne

    2012-02-01

    We characterized patterns of genetic variation in populations of the fire ant Solenopsis invicta in China using mitochondrial DNA sequences and nuclear microsatellite loci to test predictions as to how propagule pressure and subsequent dispersal following establishment jointly shape the invasion success of this ant in this recently invaded area. Fire ants in Wuchuan (Guangdong Province) are genetically differentiated from those found in other large infested areas of China. The immediate source of ants in Wuchuan appears to be somewhere near Texas, which ranks first among the southern USA infested states in the exportation of goods to China. Most colonies from spatially distant, outlying areas in China are genetically similar to one another and appear to share a common source (Wuchuan, Guangdong Province), suggesting that long-distance jump dispersal has been a prevalent means of recent spread of fire ants in China. Furthermore, most colonies at outlier sites are of the polygyne social form (featuring multiple egg-laying queens per nest), reinforcing the important role of this social form in the successful invasion of new areas and subsequent range expansion following invasion. Several analyses consistently revealed characteristic signatures of genetic bottlenecks for S. invicta populations in China. The results of this study highlight the invasive potential of this pest ant, suggest that the magnitude of international trade may serve as a predictor of propagule pressure and indicate that rates and patterns of subsequent range expansion are partly determined by the interplay between species traits and the trade and transportation networks. © Published 2011. This article is a U.S. Government work and is in the public domain in the USA.

  6. Flame Image Segmentation Based on the Bee Colony Algorithm with Characteristics of Levy Flights

    Directory of Open Access Journals (Sweden)

    Xiaolin Zhang

    2015-01-01

    Full Text Available The real-time processing of the image segmentation method with accuracy is very important in the application of the flame image detection system. This paper considers a novel method for flame image segmentation. It is the bee colony algorithm with characteristics enhancement of Levy flights against the problems of the algorithm during segmentation, including long calculation time and poor stability. By introducing the idea of Levy flights, this method designs a new local search strategy. By setting the current optimal value and based on the collaboration between the populations, it reinforces the overall convergence speed. By adopting the new fitness evaluation method and combining it with the two-dimensional entropy multithreshold segmentation principle, this paper develops a threshold segmentation test of the flame image. Test results show that this method has some advantages in terms of accuracy of threshold selection and calculation time. The robustness of the algorithm meets the actual demands in the engineering application.

  7. Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks

    Directory of Open Access Journals (Sweden)

    Yuquan Guo

    2017-01-01

    Full Text Available Community structure is important for us to understand the functions and structure of the complex networks. In this paper, Heuristic Artificial Bee Colony (HABC algorithm based on swarm intelligence is proposed for uncovering community. The proposed HABC includes initialization, employed bee searching, onlooker searching, and scout bee searching. In initialization stage, the nectar sources with simple community structure are generated through network dynamic algorithm associated with complete subgraph. In employed bee searching and onlooker searching stages, the searching function is redefined to address the community problem. The efficiency of searching progress can be improved by a heuristic function which is an average agglomerate probability of two neighbor communities. Experiments are carried out on artificial and real world networks, and the results demonstrate that HABC will have better performance in terms of comparing with the state-of-the-art algorithms.

  8. Learning from nature: Nature-inspired algorithms

    DEFF Research Database (Denmark)

    Albeanu, Grigore; Madsen, Henrik; Popentiu-Vladicescu, Florin

    2016-01-01

    During last decade, the nature has inspired researchers to develop new algorithms. The largest collection of nature-inspired algorithms is biology-inspired: swarm intelligence (particle swarm optimization, ant colony optimization, cuckoo search, bees' algorithm, bat algorithm, firefly algorithm etc...

  9. An Enhanced Artificial Bee Colony Algorithm with Solution Acceptance Rule and Probabilistic Multisearch

    Directory of Open Access Journals (Sweden)

    Alkın Yurtkuran

    2016-01-01

    Full Text Available The artificial bee colony (ABC algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA to address global optimization problems. A new solution acceptance rule is proposed where, instead of greedy selection between old solution and new candidate solution, worse candidate solutions have a probability to be accepted. Additionally, the acceptance probability of worse candidates is nonlinearly decreased throughout the search process adaptively. Moreover, in order to improve the performance of the ABC and balance the intensification and diversification, a probabilistic multisearch strategy is presented. Three different search equations with distinctive characters are employed using predetermined search probabilities. By implementing a new solution acceptance rule and a probabilistic multisearch approach, the intensification and diversification performance of the ABC algorithm is improved. The proposed algorithm has been tested on well-known benchmark functions of varying dimensions by comparing against novel ABC variants, as well as several recent state-of-the-art algorithms. Computational results show that the proposed ABC-SA outperforms other ABC variants and is superior to state-of-the-art algorithms proposed in the literature.

  10. Evaluation of Cutting Performance of Diamond Saw Machine Using Artificial Bee Colony (ABC Algorithm

    Directory of Open Access Journals (Sweden)

    Masoud Akhyani

    2017-12-01

    Full Text Available Artificial Intelligence (AI techniques are used for solving the intractable engineering problems. In this study, it is aimed to study the application of artificial bee colony algorithm for predicting the performance of circular diamond saw in sawing of hard rocks. For this purpose, varieties of fourteen types of hard rocks were cut in laboratory using a cutting rig at 5 mm depth of cut, 40 cm/min feed rate and 3000 rpm peripheral speed. Four major mechanical and physical properties of studied rocks such as uniaxial compressive strength (UCS, Schimazek abrasivity factor (SF-a, Mohs hardness (Mh, and Young’s modulus (Ym were determined in rock mechanic laboratory. Artificial bee colony (ABC was used to classify the performance of circular diamond saw based on mentioned mechanical properties of rocks. Ampere consumption and wear rate of diamond saw were selected as criteria to evaluate the result of ABC algorithm. Ampere consumption was determined during cutting process and the average wear rate of diamond saw was calculated from width, length and height loss. The results of comparison between ABC’s results and cutting performance (ampere consumption and wear rate of diamond saw indicated the ability of metaheuristic algorithm such as ABC to evaluate the cutting performance.

  11. Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

    Science.gov (United States)

    Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

    2017-01-01

    The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

  12. Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

    Science.gov (United States)

    Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

    2014-05-01

    Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

  13. Mobile Ad Hoc Network Energy Cost Algorithm Based on Artificial Bee Colony

    Directory of Open Access Journals (Sweden)

    Mustafa Tareq

    2017-01-01

    Full Text Available A mobile ad hoc network (MANET is a collection of mobile nodes that dynamically form a temporary network without using any existing network infrastructure. MANET selects a path with minimal number of intermediate nodes to reach the destination node. As the distance between each node increases, the quantity of transmission power increases. The power level of nodes affects the simplicity with which a route is constituted between a couple of nodes. This study utilizes the swarm intelligence technique through the artificial bee colony (ABC algorithm to optimize the energy consumption in a dynamic source routing (DSR protocol in MANET. The proposed algorithm is called bee DSR (BEEDSR. The ABC algorithm is used to identify the optimal path from the source to the destination to overcome energy problems. The performance of the BEEDSR algorithm is compared with DSR and bee-inspired protocols (BeeIP. The comparison was conducted based on average energy consumption, average throughput, average end-to-end delay, routing overhead, and packet delivery ratio performance metrics, varying the node speed and packet size. The BEEDSR algorithm is superior in performance than other protocols in terms of energy conservation and delay degradation relating to node speed and packet size.

  14. An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Xuanhu He

    2015-03-01

    Full Text Available Optimal power flow (OPF objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity; tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable.

  15. Colony density and activity times of the ant Camponotus semitestaceus (Hymenoptera: formicidae) in a shrub steppe community

    Energy Technology Data Exchange (ETDEWEB)

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (anti-x +/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites an

  16. Artificial bee colony algorithm for economic load dispatch with wind power energy

    Directory of Open Access Journals (Sweden)

    Safari Amin

    2016-01-01

    Full Text Available This paper presents an efficient Artificial Bee Colony (ABC algorithm for solving large scale economic load dispatch (ELD problems in power networks. To realize the ELD, the valve-point loading effect, system load demand, power losses, ramp rate limits and prohibited operation zones are considered here. Simulations were performed on four different power systems with 3, 6, 15 and 40 generating units and the results are compared with two forms of power systems, one power system is with a wind power generator and other power system is without a wind power generator. The results of this study reveal that the proposed approach is able to find appreciable ELD solutions than those of previous algorithms.

  17. Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

    Directory of Open Access Journals (Sweden)

    Guo Jiansheng

    2014-12-01

    Full Text Available Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.

  18. Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

    Science.gov (United States)

    Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

    2016-01-01

    Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

  19. Journal Bearing Optimization Using Nonsorted Genetic Algorithm and Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    L. Gorasso

    2014-05-01

    Full Text Available In this work, a journal bearing optimization process has been developed and is divided into two stages. Each one has a set of decision variables and custom objectives aggregating performances with a weighting strategy. The performance functions used are an artificial neural network, trained with Reynolds equation solutions, and a CFD simulation of the bearings carried out with commercial software. The results show the capabilities of the algorithm to design and optimize journal bearings by reducing both power loss and mass flow with respect to ones designed with traditional methods, as well as by minimizing the maximum and average temperature.

  20. Design of fuzzy classifier for diabetes disease using Modified Artificial Bee Colony algorithm.

    Science.gov (United States)

    Beloufa, Fayssal; Chikh, M A

    2013-10-01

    In this study, diagnosis of diabetes disease, which is one of the most important diseases, is conducted with artificial intelligence techniques. We have proposed a novel Artificial Bee Colony (ABC) algorithm in which a mutation operator is added to an Artificial Bee Colony for improving its performance. When the current best solution cannot be updated, a blended crossover operator (BLX-α) of genetic algorithm is applied, in order to enhance the diversity of ABC, without compromising with the solution quality. This modified version of ABC is used as a new tool to create and optimize automatically the membership functions and rules base directly from data. We take the diabetes dataset used in our work from the UCI machine learning repository. The performances of the proposed method are evaluated through classification rate, sensitivity and specificity values using 10-fold cross-validation method. The obtained classification rate of our method is 84.21% and it is very promising when compared with the previous research in the literature for the same problem. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  1. Ant Colony Algorithms for the Resolution of Semantic Searches in P2P Networks

    OpenAIRE

    Krynicki, Kamil Krzysztof

    2016-01-01

    [EN] The long-lasting trend in the field of computation of stress and resource distribution has found its way into computer networks via the concept of peer-to-peer (P2P) connectivity. P2P is a symmetrical model, where each network node is enabled a comparable range of capacities and resources. It stands in a stark contrast to the classical, strongly asymmetrical client-server approach. P2P, originally considered only a complimentary, server-side structure to the straightforward client-server...

  2. Ant Colony Optimization Algorithm to Dynamic Energy Management in Cloud Data Center

    Directory of Open Access Journals (Sweden)

    Shanchen Pang

    2017-01-01

    Full Text Available With the wide deployment of cloud computing data centers, the problems of power consumption have become increasingly prominent. The dynamic energy management problem in pursuit of energy-efficiency in cloud data centers is investigated. Specifically, a dynamic energy management system model for cloud data centers is built, and this system is composed of DVS Management Module, Load Balancing Module, and Task Scheduling Module. According to Task Scheduling Module, the scheduling process is analyzed by Stochastic Petri Net, and a task-oriented resource allocation method (LET-ACO is proposed, which optimizes the running time of the system and the energy consumption by scheduling tasks. Simulation studies confirm the effectiveness of the proposed system model. And the simulation results also show that, compared to ACO, Min-Min, and RR scheduling strategy, the proposed LET-ACO method can save up to 28%, 31%, and 40% energy consumption while meeting performance constraints.

  3. The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch

    International Nuclear Information System (INIS)

    Secui, Dinu Calin

    2015-01-01

    This paper suggests a chaotic optimizing method, based on the GBABC (global best artificial bee colony algorithm), where the random sequences used in updating the solutions of this algorithm are replaced with chaotic sequences generated by chaotic maps. The new algorithm, called chaotic CGBABC (global best artificial bee colony algorithm), is used to solving the multi-area economic/emission dispatch problem taking into consideration the valve-point effects, the transmission line losses, multi-fuel sources, prohibited operating zones, tie line capacity and power transfer cost between different areas of the system. The behaviour of the CGBABC algorithm is studied considering ten chaotic maps both one-dimensional and bi-dimensional, with various probability density functions. The CGBABC algorithm's performance including a variety of chaotic maps is tested on five systems (6-unit, 10-unit, 16-unit, 40-unit and 120-unit) with different characteristics, constraints and sizes. The results comparison highlights a hierarchy in the chaotic maps included in the CGBABC algorithm and shows that it performs better than the classical ABC algorithm, the GBABC algorithm and other optimization techniques. - Highlights: • A chaotic global best ABC algorithm (CGBABC) is presented. • CGBABC is applied for solving the multi-area economic/emission dispatch problem. • Valve-point effects, multi-fuel sources, POZ, transmission losses were considered. • The algorithm is tested on five systems having 6, 10, 16, 40 and 120 thermal units. • CGBABC algorithm outperforms several optimization techniques.

  4. Use of artificial bee colonies algorithm as numerical approximation of differential equations solution

    Science.gov (United States)

    Fikri, Fariz Fahmi; Nuraini, Nuning

    2018-03-01

    The differential equation is one of the branches in mathematics which is closely related to human life problems. Some problems that occur in our life can be modeled into differential equations as well as systems of differential equations such as the Lotka-Volterra model and SIR model. Therefore, solving a problem of differential equations is very important. Some differential equations are difficult to solve, so numerical methods are needed to solve that problems. Some numerical methods for solving differential equations that have been widely used are Euler Method, Heun Method, Runge-Kutta and others. However, some of these methods still have some restrictions that cause the method cannot be used to solve more complex problems such as an evaluation interval that we cannot change freely. New methods are needed to improve that problems. One of the method that can be used is the artificial bees colony algorithm. This algorithm is one of metaheuristic algorithm method, which can come out from local search space and do exploration in solution search space so that will get better solution than other method.

  5. Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation

    Science.gov (United States)

    Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.

    In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.

  6. An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2011-09-01

    Full Text Available Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the stochastic job shop scheduling problem (SJSSP has not received sufficient attention. In this paper, we propose an artificial bee colony (ABC algorithm for SJSSP with the objective of minimizing the maximum lateness (which is an index of service quality. First, we propose a performance estimate for preliminary screening of the candidate solutions. Then, the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation (through Monte Carlo simulation process. Finally, the computational results on different-scale test problems validate the effectiveness and efficiency of the proposed approach.

  7. An Improved Artificial Colony Algorithm Model for Forecasting Chinese Electricity Consumption and Analyzing Effect Mechanism

    Directory of Open Access Journals (Sweden)

    Jingmin Wang

    2016-01-01

    Full Text Available Electricity consumption forecast is perceived to be a growing hot topic in such a situation that China’s economy has entered a period of new normal and the demand of electric power has slowed down. Therefore, exploring Chinese electricity consumption influence mechanism and forecasting electricity consumption are crucial to formulate electrical energy plan scientifically and guarantee the sustainable economic and social development. Research has identified medium and long term electricity consumption forecast as a difficult study influenced by various factors. This paper proposed an improved Artificial Bee Colony (ABC algorithm which combined with multivariate linear regression (MLR for exploring the influencing mechanism of various factors on Chinese electricity consumption and forecasting electricity consumption in the future. The results indicated that the improved ABC algorithm in view of the various factors is superior to traditional models just considering unilateralism in accuracy and persuasion. The overall findings cast light on this model which provides a new scientific and effective way to forecast the medium and long term electricity consumption.

  8. WEB NEWS DOCUMENTS CLUSTERING IN INDONESIAN LANGUAGE USING SINGULAR VALUE DECOMPOSITION-PRINCIPAL COMPONENT ANALYSIS (SVDPCA AND ANT ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Arif Fadllullah

    2016-02-01

    Full Text Available Ant-based document clustering is a cluster method of measuring text documents similarity based on the shortest path between nodes (trial phase and determines the optimal clusters of sequence document similarity (dividing phase. The processing time of trial phase Ant algorithms to make document vectors is very long because of high dimensional Document-Term Matrix (DTM. In this paper, we proposed a document clustering method for optimizing dimension reduction using Singular Value Decomposition-Principal Component Analysis (SVDPCA and Ant algorithms. SVDPCA reduces size of the DTM dimensions by converting freq-term of conventional DTM to score-pc of Document-PC Matrix (DPCM. Ant algorithms creates documents clustering using the vector space model based on the dimension reduction result of DPCM. The experimental results on 506 news documents in Indonesian language demonstrated that the proposed method worked well to optimize dimension reduction up to 99.7%. We could speed up execution time efficiently of the trial phase and maintain the best F-measure achieved from experiments was 0.88 (88%.

  9. A hybrid evolutionary algorithm for distribution feeder reconfiguration

    Indian Academy of Sciences (India)

    FAPSO) and ant colony optimization (ACO), called HFAPSO, is proposed to solve it. The performance of HFAPSO is evaluated and compared with other methods such as genetic algorithm (GA), ACO, the original PSO, Hybrid PSO and ACO.

  10. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey

    International Nuclear Information System (INIS)

    Uzlu, Ergun; Akpınar, Adem; Özturk, Hasan Tahsin; Nacar, Sinan; Kankal, Murat

    2014-01-01

    The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the classical ANN trained with the BP algorithm. Furthermore, results indicated future hydroelectric generation in Turkey will range from 69.1 to 76.5 TWh in 2021, and the total annual electricity demand represented by hydropower supply rates will range from 14.8% to 18.0%. However, according to Vision 2023 agenda goals, the country plans to produce 30% of its electricity demand from renewable energy sources by 2023, and use 20% less energy than in 2010. This percentage renewable energy provision cannot be accomplished unless changes in energy policy and investments are not addressed and implemented. In order to achieve this goal, the Turkish government must reconsider and raise its own investments in hydropower, wind, solar, and geothermal energy, particularly hydropower. - Highlights: • This study is associated with predicting hydropower generation in Turkey. • Sensitivity analysis was performed to determine predictor variables. • GEED, population, energy consumption and AYT were used as predictor variables. • ANN-ABC predicted the hydropower generation more accurately

  11. Context-dependent expression of the foraging gene in field colonies of ants: the interacting roles of age, environment and task.

    Science.gov (United States)

    Ingram, Krista K; Gordon, Deborah M; Friedman, Daniel A; Greene, Michael; Kahler, John; Peteru, Swetha

    2016-08-31

    Task allocation among social insect workers is an ideal framework for studying the molecular mechanisms underlying behavioural plasticity because workers of similar genotype adopt different behavioural phenotypes. Elegant laboratory studies have pioneered this effort, but field studies involving the genetic regulation of task allocation are rare. Here, we investigate the expression of the foraging gene in harvester ant workers from five age- and task-related groups in a natural population, and we experimentally test how exposure to light affects foraging expression in brood workers and foragers. Results from our field study show that the regulation of the foraging gene in harvester ants occurs at two time scales: levels of foraging mRNA are associated with ontogenetic changes over weeks in worker age, location and task, and there are significant daily oscillations in foraging expression in foragers. The temporal dissection of foraging expression reveals that gene expression changes in foragers occur across a scale of hours and the level of expression is predicted by activity rhythms: foragers have high levels of foraging mRNA during daylight hours when they are most active outside the nests. In the experimental study, we find complex interactions in foraging expression between task behaviour and light exposure. Oscillations occur in foragers following experimental exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar conditions. No significant differences were seen in foraging expression over time in either task in 24 h dark (DD) conditions. Interestingly, the expression of foraging in both undisturbed field and experimentally treated foragers is also significantly correlated with the expression of the circadian clock gene, cycle Our results provide evidence that the regulation of this gene is context-dependent and associated with both ontogenetic and daily behavioural plasticity in field colonies of harvester ants. Our results underscore

  12. An artificial bee colony algorithm for the capacitated vehicle routing problem

    DEFF Research Database (Denmark)

    Szeto, W.Y.; Wu, Yongzhong; Ho, Sin C.

    2011-01-01

    This paper introduces an artificial bee colony heuristic for solving the capacitated vehicle routing problem. The artificial bee colony heuristic is a swarm-based heuristic, which mimics the foraging behavior of a honey bee swarm. An enhanced version of the artificial bee colony heuristic is also...

  13. Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization

    Directory of Open Access Journals (Sweden)

    Jian-Guo Zheng

    2015-01-01

    Full Text Available Artificial bee colony (ABC algorithm is a popular swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. However, ABC is good at exploration but poor at exploitation and its convergence speed is also an issue in some cases. To improve the performance of ABC, a novel ABC combined with grenade explosion method (GEM and Cauchy operator, namely, ABCGC, is proposed. GEM is embedded in the onlooker bees’ phase to enhance the exploitation ability and accelerate convergence of ABCGC; meanwhile, Cauchy operator is introduced into the scout bees’ phase to help ABCGC escape from local optimum and further enhance its exploration ability. Two sets of well-known benchmark functions are used to validate the better performance of ABCGC. The experiments confirm that ABCGC is significantly superior to ABC and other competitors; particularly it converges to the global optimum faster in most cases. These results suggest that ABCGC usually achieves a good balance between exploitation and exploration and can effectively serve as an alternative for global optimization.

  14. Worker lifespan is an adaptive trait during colony establishment in the long-lived ant Lasius niger

    NARCIS (Netherlands)

    Kramer, Boris H.; Schaible, Ralf; Scheuerlein, Alexander

    2016-01-01

    Eusociality has been recognized as a strong driver of lifespan evolution. While queens show extraordinary lifespans of 20 years and more, worker lifespan is short and variable. A recent comparative study found that in eusocial species with larger average colony sizes the disparities in the lifespans

  15. Optimization of fuel reloads for a BWR using the ant colony system; Optimizacion de recargas de combustible para un BWR usando el sistema de colonia de hormigas

    Energy Technology Data Exchange (ETDEWEB)

    Esquivel E, J. [Universidad Autonoma del Estado de Mexico, Facultad de Ingenieria, Cerro de Coatepec s/n, Ciudad Universitaria, 50110 Toluca, Estado de Mexico (Mexico); Ortiz S, J. J. [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)], e-mail: jaime.es.jaime@gmail.com

    2009-10-15

    In this work some results obtained during the development of optimization systems are presented, which are employees for the fuel reload design in a BWR. The systems use the ant colony optimization technique. As first instance, a system is developed that was adapted at travel salesman problem applied for the 32 state capitals of Mexican Republic. The purpose of this implementation is that a similarity exists with the design of fuel reload, since the two problems are of combinatorial optimization with decision variables that have similarity between both. The system was coupled to simulator SIMULATE-3, obtaining good results when being applied to an operation cycle in equilibrium for reactors of nuclear power plant of Laguna Verde. (Author)

  16. An enhanced artificial bee colony algorithm (EABC for solving dispatching of hydro-thermal system (DHTS problem.

    Directory of Open Access Journals (Sweden)

    Yi Yu

    Full Text Available The dispatching of hydro-thermal system is a nonlinear programming problem with multiple constraints and high dimensions and the solution techniques of the model have been a hotspot in research. Based on the advantage of that the artificial bee colony algorithm (ABC can efficiently solve the high-dimensional problem, an improved artificial bee colony algorithm has been proposed to solve DHTS problem in this paper. The improvements of the proposed algorithm include two aspects. On one hand, local search can be guided in efficiency by the information of the global optimal solution and its gradient in each generation. The global optimal solution improves the search efficiency of the algorithm but loses diversity, while the gradient can weaken the loss of diversity caused by the global optimal solution. On the other hand, inspired by genetic algorithm, the nectar resource which has not been updated in limit generation is transformed to a new one by using selection, crossover and mutation, which can ensure individual diversity and make full use of prior information for improving the global search ability of the algorithm. The two improvements of ABC algorithm are proved to be effective via a classical numeral example at last. Among which the genetic operator for the promotion of the ABC algorithm's performance is significant. The results are also compared with those of other state-of-the-art algorithms, the enhanced ABC algorithm has general advantages in minimum cost, average cost and maximum cost which shows its usability and effectiveness. The achievements in this paper provide a new method for solving the DHTS problems, and also offer a novel reference for the improvement of mechanism and the application of algorithms.

  17. An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

    Science.gov (United States)

    Li, Bai; Gong, Li-gang; Yang, Wen-lun

    2014-01-01

    Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

  18. An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning

    Directory of Open Access Journals (Sweden)

    Bai Li

    2014-01-01

    Full Text Available Unmanned combat aerial vehicles (UCAVs have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC algorithm improved by a balance-evolution strategy (BES is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

  19. Colony density and activity times of the ant Camponotus semitestaceus (hymenoptera:formicidae) in a shrub steppe community

    Energy Technology Data Exchange (ETDEWEB)

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (x +/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites and 0.028 +/- 0.028 per m/sup 2/ on a burned site. Seventy-five percent of the nest entrances were located alongside the stems of sagebrush, indicating a preference for these microhabitats as nest locations. Above-ground activity times were determined by using time lapse photography. Activity commenced shortly after sunset, when light intensities dropped to 2.5 to 1.0 foot-candles (ca. 27 to 11 lux) and terminated just before sunrise. Light intensity appears to be the primary cue for controlling above-ground activity periods of this species, but temperature also appears to be an important factor. When soil surface temperatures drop to 1.7 to 3.9/sup 0/C, all above-ground activity ceases, irrespective of light intensity. 19 references, 3 figures, 2 tables.

  20. Colony density and activity times of the ant Camponotus semitestaceus (hymenoptera: Formicidae) in a shrub steppe community

    Energy Technology Data Exchange (ETDEWEB)

    Gano, K.A.; Rogers, L.E.

    1983-11-01

    Colony densities and above-ground activity periods were determined for Camponotus semitestaceus colonies within a shrub-steppe community. Colony densities (anti x=/- SD) averaged 0.088 +/- 0.032 per m/sup 2/ and 0.048 +/- 0.028 per m/sup 2/ on two sagebrush-bunchgrass sites and 0.028 +/- 0.028 per m/sup 2/ on a burned site. Seventy-five percent of the nest entrances were located alongside the stems of sagebrush, indicating a preference for these microhabitats as nest locations. Above-ground activity times were determined by using time lapse photography. Activity commenced shortly after sunset, when light intensities dropped to 2.5 to 1.0 foot-candles (ca. 27 to 11 lux) and terminated just before sunrise. Light intensity appears to be the primary cue for controlling above-ground activity periods of this species, but temperature also appears to be an important factor. When soil surface temperatures drop to 1.7 to 3.9/sup 0/C, all above-ground activity ceases, irrespective of light intensity.

  1. Multi-criteria ACO-based Algorithm for Ship’s Trajectory Planning

    OpenAIRE

    Agnieszka Lazarowska

    2017-01-01

    The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a ...

  2. Voltage Profile Enhancement and Reduction of Real Power loss by Hybrid Biogeography Based Artificial Bee Colony algorithm

    Directory of Open Access Journals (Sweden)

    K. Lenin

    2014-04-01

    Full Text Available This paper presents Hybrid Biogeography algorithm for solving the multi-objective reactive power dispatch problem in a power system. Real Power Loss minimization and maximization of voltage stability margin are taken as the objectives. Artificial bee colony optimization (ABC is quick and forceful algorithm for global optimization. Biogeography-Based Optimization (BBO is a new-fangled biogeography inspired algorithm. It mainly utilizes the biogeography-based relocation operator to share the information among solutions. In this work, a hybrid algorithm with BBO and ABC is projected, and named as HBBABC (Hybrid Biogeography based Artificial Bee Colony Optimization, for the universal numerical optimization problem. HBBABC merge the searching behavior of ABC with that of BBO. Both the algorithms have different solution probing tendency like ABC have good exploration probing tendency while BBO have good exploitation probing tendency.  HBBABC used to solve the reactive power dispatch problem and the proposed technique has been tested in standard IEEE30 bus test system.

  3. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    Directory of Open Access Journals (Sweden)

    Ahmed F. Mohamed

    2014-05-01

    Full Text Available One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC. The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  4. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    Science.gov (United States)

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  5. Collective search by ants in microgravity

    Directory of Open Access Journals (Sweden)

    Stefanie M. Countryman

    2015-03-01

    Full Text Available The problem of collective search is a tradeoff between searching thoroughly and covering as much area as possible. This tradeoff depends on the density of searchers. Solutions to the problem of collective search are currently of much interest in robotics and in the study of distributed algorithms, for example to design ways that without central control robots can use local information to perform search and rescue operations. Ant colonies operate without central control. Because they can perceive only local, mostly chemical and tactile cues, they must search collectively to find resources and to monitor the colony's environment. Examining how ants in diverse environments solve the problem of collective search can elucidate how evolution has led to diverse forms of collective behavior. An experiment on the International Space Station in January 2014 examined how ants (Tetramorium caespitum perform collective search in microgravity. In the ISS experiment, the ants explored a small arena in which a barrier was lowered to increase the area and thus lower ant density. In microgravity, relative to ground controls, ants explored the area less thoroughly and took more convoluted paths. It appears that the difficulty of holding on to the surface interfered with the ants’ ability to search collectively. Ants frequently lost contact with the surface, but showed a remarkable ability to regain contact with the surface.

  6. VLSI PARTITIONING ALGORITHM WITH ADAPTIVE CONTROL PARAMETER

    Directory of Open Access Journals (Sweden)

    P. N. Filippenko

    2013-03-01

    Full Text Available The article deals with the problem of very large-scale integration circuit partitioning. A graph is selected as a mathematical model describing integrated circuit. Modification of ant colony optimization algorithm is presented, which is used to solve graph partitioning problem. Ant colony optimization algorithm is an optimization method based on the principles of self-organization and other useful features of the ants’ behavior. The proposed search system is based on ant colony optimization algorithm with the improved method of the initial distribution and dynamic adjustment of the control search parameters. The experimental results and performance comparison show that the proposed method of very large-scale integration circuit partitioning provides the better search performance over other well known algorithms.

  7. MULTIPLE ANT COLONY SYSTEM FOR A VRP WITH TIME WINDOWS AND SCHEDULED LOADING MÚLTIPLES SISTEMAS DE COLONIAS DE HORMIGAS PARA UN VRP CON VENTANAS DE TIEMPO Y PROGRAMACIÓN DE LA CARGA

    Directory of Open Access Journals (Sweden)

    Pablo Ortega

    2009-12-01

    Full Text Available The vehicle routing problem with time windows and scheduled loading [VRPTWSL] requires not only the design of routes with time windows and capacity constraints, but also a schedule of the departures of vehicles from the depot given a load time due to the limited resources available to load the demand in the vehicles. A mathematical formulation of the vehicle routing problem with time windows and scheduled loading is presented and a metaheuristics based on Multiple Ant Colony System is proposed and implemented where two ant colonies, each with a single objective function, are organized in a hierarchical way. A time update procedure is incorporated into the ant constructive procedure to update and schedule the departure of a vehicle from the depot when each ant moves to a new customer-node. Constraint programming is used to determine a feasible move to a new customer-node. As [VRPTWSL] incorporates the vehicle departure scheduling, the algorithm presented in this paper has a direct application to real problems, in this way [VRPTWSL] can be taken as an important advance for practical vehicle routing problems.El problema de rutas para vehículos con ventanas de tiempo y programación de la carga no solo requiere el diseño de las rutas que satisfagan las restricciones temporales y de capacidad de los vehículos sino que también la programación de las salidas de los vehículos desde un terminal dado un tiempo de carga debido a los recursos limitados disponibles para cargar las demandas de los clientes en los vehículos. No solo se presenta una formulación del problema de diseño de rutas para vehículos con ventanas de tiempo y programación de la carga, sino que también se propone e implementa una metaheurística basada en múltiples sistemas de colonias de hormigas, cada una con una sola función objetivo, organizadas de manera jerárquica. Se incorpora una forma de actualización de tiempo dentro del procedimiento constructivo para actualizar

  8. Artificial Bee Colony Algorithm Merged with Pheromone Communication Mechanism for the 0-1 Multidimensional Knapsack Problem

    Directory of Open Access Journals (Sweden)

    Junzhong Ji

    2013-01-01

    Full Text Available Given a set of n objects, the objective of the 0-1 multidimensional knapsack problem (MKP_01 is to find a subset of the object set that maximizes the total profit of the objects in the subset while satisfying m knapsack constraints. In this paper, we have proposed a new artificial bee colony (ABC algorithm for the MKP_01. The new ABC algorithm introduces a novel communication mechanism among bees, which bases on the updating and diffusion of inductive pheromone produced by bees. In a number of experiments and comparisons, our approach obtains better quality solutions in shorter time than the ABC algorithm without the mechanism. We have also compared the solution performance of our approach against some stochastic approaches recently reported in the literature. Computational results demonstrate the superiority of the new ABC approach over all the other approaches.

  9. Biobjective Optimization of Vibration Performance of Steel-Spring Floating Slab Tracks by Four-Pole Parameter Method Coupled with Ant Colony Optimization

    Directory of Open Access Journals (Sweden)

    Hao Jin

    2015-01-01

    Full Text Available Steel-spring floating slab tracks are one of the most effective methods to reduce vibrations from underground railways, which has drawn more and more attention in scientific communities. In this paper, the steel-spring floating slab track located in Track Vibration Abatement and Control Laboratory was modeled with four-pole parameter method. The influences of the fastener damping ratio, the fastener stiffness, the steel-spring damping ratio, and the steel-spring stiffness were researched for the rail displacement and the foundation acceleration. Results show that the rail displacement and the foundation acceleration will decrease with the increase of the fastener stiffness or the steel-spring damping ratio. However, the rail displacement and the foundation acceleration have the opposite variation tendency for the fastener damping ratio and the steel-spring stiffness. In order to optimize the rail displacement and the foundation acceleration affected by the fastener damping ratio and the steel-spring stiffness at the same time, a multiobjective ant colony optimization (ACO was employed. Eventually, Pareto optimal frontier of the rail displacement and the foundation acceleration was derived. Furthermore, the desirable values of the fastener damping ratio and the steel-spring stiffness can be obtained according to the corresponding Pareto optimal solution set.

  10. Aplicación del Método de la Colonia de Hormigas Mixto a la optimización de intercambiadores de calor de tubo y coraza//Application of the Mixed Ant Colony Method to the optimization of tube and shell heat exchangers

    Directory of Open Access Journals (Sweden)

    Maida Bárbara Reyes‐Rodríguez

    2014-05-01

    Full Text Available Los procesos de transferencia de calor sonuno de los problemas más importantes a resolver en el campo de la Ingeniería. Entre los equipos más usados en la industria para realizar la transferencia de calor están los intercambiadores de calor de tubo y coraza. En el presente trabajo se desarrolla el procedimiento para la optimización del diseño de estos equipos utilizando el método de Kern y aplicando el algoritmo de la colonia de hormigas. Se aplica el mismo a tres ejemplos concretos y los resultados obtenidos se comparan con los obtenidos aplicando otros métodos de la inteligencia artificial. Se optimizan los principales parámetros geométricos de los intercambiadores de calor de tubo y coraza para lograr un menor costo de los mismos. Se demuestra la eficacia del nuevo procedimiento MACO (Mixed Ant Colony Optimization, en el proceso de optimización desde el punto de vista económico utilizando diferentes casos de estudios.Palabras claves: intercambiadores de calor, colonia de hormigas, método de Kern.______________________________________________________________________________AbstractHeat transfer processes are one of the most important problems to be solved in the field of Engineering. Among the most widely used equipment for heat transfer in the industry are the shell and tube heat exchangers. This paper develops the procedure for optimizing the design of shell and tube heat exchangers using the method of Kern and applying the ant colony algorithm. The procedure has been applied to three specific examples and the results obtained are compared with those obtained by applying other methods of artificial intelligence. The main geometric parameters of shell and tube heat exchangers are optimized, to achieve a lower cost of the exchanger. The efficacy of the new procedure MACO (Mixed Ant Colony Optimization for the optimization process from economically point of view was demonstrated, using different case studies.Key words: heat

  11. An Enhanced Discrete Artificial Bee Colony Algorithm to Minimize the Total Flow Time in Permutation Flow Shop Scheduling with Limited Buffers

    Directory of Open Access Journals (Sweden)

    Guanlong Deng

    2016-01-01

    Full Text Available This paper presents an enhanced discrete artificial bee colony algorithm for minimizing the total flow time in the flow shop scheduling problem with buffer capacity. First, the solution in the algorithm is represented as discrete job permutation to directly convert to active schedule. Then, we present a simple and effective scheme called best insertion for the employed bee and onlooker bee and introduce a combined local search exploring both insertion and swap neighborhood. To validate the performance of the presented algorithm, a computational campaign is carried out on the Taillard benchmark instances, and computations and comparisons show that the proposed algorithm is not only capable of solving the benchmark set better than the existing discrete differential evolution algorithm and iterated greedy algorithm, but also capable of performing better than two recently proposed discrete artificial bee colony algorithms.

  12. Discovery of Transition Rules for Cellular Automata Using Artificial Bee Colony and Particle Swarm Optimization Algorithms in Urban Growth Modeling

    Directory of Open Access Journals (Sweden)

    Fereydoun Naghibi

    2016-12-01

    Full Text Available This paper presents an advanced method in urban growth modeling to discover transition rules of cellular automata (CA using the artificial bee colony (ABC optimization algorithm. Also, comparisons between the simulation results of CA models optimized by the ABC algorithm and the particle swarm optimization algorithms (PSO as intelligent approaches were performed to evaluate the potential of the proposed methods. According to previous studies, swarm intelligence algorithms for solving optimization problems such as discovering transition rules of CA in land use change/urban growth modeling can produce reasonable results. Modeling of urban growth as a dynamic process is not straightforward because of the existence of nonlinearity and heterogeneity among effective involved variables which can cause a number of challenges for traditional CA. ABC algorithm, the new powerful swarm based optimization algorithms, can be used to capture optimized transition rules of CA. This paper has proposed a methodology based on remote sensing data for modeling urban growth with CA calibrated by the ABC algorithm. The performance of ABC-CA, PSO-CA, and CA-logistic models in land use change detection is tested for the city of Urmia, Iran, between 2004 and 2014. Validations of the models based on statistical measures such as overall accuracy, figure of merit, and total operating characteristic were made. We showed that the overall accuracy of the ABC-CA model was 89%, which was 1.5% and 6.2% higher than those of the PSO-CA and CA-logistic model, respectively. Moreover, the allocation disagreement (simulation error of the simulation results for the ABC-CA, PSO-CA, and CA-logistic models are 11%, 12.5%, and 17.2%, respectively. Finally, for all evaluation indices including running time, convergence capability, flexibility, statistical measurements, and the produced spatial patterns, the ABC-CA model performance showed relative improvement and therefore its superiority was

  13. Optimization-Based Artificial Bee Colony Algorithm for Data Collection in Large-Scale Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yinggao Yue

    2016-01-01

    Full Text Available Data collection is a fundamental operation in various mobile wireless sensor networks (MWSN applications. The energy of nodes around the Sink can be untimely depleted owing to the fact that sensor nodes must transmit vast amounts of data, readily forming a bottleneck in energy consumption; mobile wireless sensor networks have been designed to address this issue. In this study, we focused on a large-scale and intensive MWSN which allows a certain amount of data latency by investigating mobile Sink balance from three aspects: data collection maximization, mobile path length minimization, and network reliability optimization. We also derived a corresponding formula to represent the MWSN and proved that it represents an NP-hard problem. Traditional data collection methods only focus on increasing the amount data collection or reducing the overall network energy consumption, which is why we designed the proposed heuristic algorithm to jointly consider cluster head selection, the routing path from ordinary nodes to the cluster head node, and mobile Sink path planning optimization. The proposed data collection algorithm for mobile Sinks is, in effect, based on artificial bee colony. Simulation results show that, in comparison with other algorithms, the proposed algorithm can effectively reduce data transmission, save energy, improve network data collection efficiency and reliability, and extend the network lifetime.

  14. Avoidance of plants unsuitable for the symbiotic fungus in leaf-cutting ants: Learning can take place entirely at the colony dump.

    Directory of Open Access Journals (Sweden)

    Andrés Arenas

    Full Text Available Plants initially accepted by foraging leaf-cutting ants are later avoided if they prove unsuitable for their symbiotic fungus. Plant avoidance is mediated by the waste produced in the fungus garden soon after the incorporation of the unsuitable leaves, as foragers can learn plant odors and cues from the damaged fungus that are both present in the recently produced waste particles. We asked whether avoidance learning of plants unsuitable for the symbiotic fungus can take place entirely at the colony dump. In order to investigate whether cues available in the waste chamber induce plant avoidance in naïve subcolonies, we exchanged the waste produced by subcolonies fed either fungicide-treated privet leaves or untreated leaves and measured the acceptance of untreated privet leaves before and after the exchange of waste. Second, we evaluated whether foragers could perceive the avoidance cues directly at the dump by quantifying the visits of labeled foragers to the waste chamber. Finally, we asked whether foragers learn to specifically avoid untreated leaves of a plant after a confinement over 3 hours in the dump of subcolonies that were previously fed fungicide-treated leaves of that species. After the exchange of the waste chambers, workers from subcolonies that had access to waste from fungicide-treated privet leaves learned to avoid that plant. One-third of the labeled foragers visited the dump. Furthermore, naïve foragers learned to avoid a specific, previously unsuitable plant if exposed solely to cues of the dump during confinement. We suggest that cues at the dump enable foragers to predict the unsuitable effects of plants even if they had never been experienced in the fungus garden.

  15. Avoidance of plants unsuitable for the symbiotic fungus in leaf-cutting ants: Learning can take place entirely at the colony dump.

    Science.gov (United States)

    Arenas, Andrés; Roces, Flavio

    2017-01-01

    Plants initially accepted by foraging leaf-cutting ants are later avoided if they prove unsuitable for their symbiotic fungus. Plant avoidance is mediated by the waste produced in the fungus garden soon after the incorporation of the unsuitable leaves, as foragers can learn plant odors and cues from the damaged fungus that are both present in the recently produced waste particles. We asked whether avoidance learning of plants unsuitable for the symbiotic fungus can take place entirely at the colony dump. In order to investigate whether cues available in the waste chamber induce plant avoidance in naïve subcolonies, we exchanged the waste produced by subcolonies fed either fungicide-treated privet leaves or untreated leaves and measured the acceptance of untreated privet leaves before and after the exchange of waste. Second, we evaluated whether foragers could perceive the avoidance cues directly at the dump by quantifying the visits of labeled foragers to the waste chamber. Finally, we asked whether foragers learn to specifically avoid untreated leaves of a plant after a confinement over 3 hours in the dump of subcolonies that were previously fed fungicide-treated leaves of that species. After the exchange of the waste chambers, workers from subcolonies that had access to waste from fungicide-treated privet leaves learned to avoid that plant. One-third of the labeled foragers visited the dump. Furthermore, naïve foragers learned to avoid a specific, previously unsuitable plant if exposed solely to cues of the dump during confinement. We suggest that cues at the dump enable foragers to predict the unsuitable effects of plants even if they had never been experienced in the fungus garden.

  16. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    Directory of Open Access Journals (Sweden)

    Mustafa Serter Uzer

    2013-01-01

    Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

  17. Artificial Bee Colony Algorithm Based on K-Means Clustering for Multiobjective Optimal Power Flow Problem

    Directory of Open Access Journals (Sweden)

    Liling Sun

    2015-01-01

    Full Text Available An improved multiobjective ABC algorithm based on K-means clustering, called CMOABC, is proposed. To fasten the convergence rate of the canonical MOABC, the way of information communication in the employed bees’ phase is modified. For keeping the population diversity, the multiswarm technology based on K-means clustering is employed to decompose the population into many clusters. Due to each subcomponent evolving separately, after every specific iteration, the population will be reclustered to facilitate information exchange among different clusters. Application of the new CMOABC on several multiobjective benchmark functions shows a marked improvement in performance over the fast nondominated sorting genetic algorithm (NSGA-II, the multiobjective particle swarm optimizer (MOPSO, and the multiobjective ABC (MOABC. Finally, the CMOABC is applied to solve the real-world optimal power flow (OPF problem that considers the cost, loss, and emission impacts as the objective functions. The 30-bus IEEE test system is presented to illustrate the application of the proposed algorithm. The simulation results demonstrate that, compared to NSGA-II, MOPSO, and MOABC, the proposed CMOABC is superior for solving OPF problem, in terms of optimization accuracy.

  18. Thermodynamic Optimization of a Geothermal- Based Organic Rankine Cycle System Using an Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Osman Özkaraca

    2017-10-01

    Full Text Available Geothermal energy is a renewable form of energy, however due to misuse, processing and management issues, it is necessary to use the resource more efficiently. To increase energy efficiency, energy systems engineers carry out careful energy control studies and offer alternative solutions. With this aim, this study was conducted to improve the performance of a real operating air-cooled organic Rankine cycle binary geothermal power plant (GPP and its components in the aspects of thermodynamic modeling, exergy analysis and optimization processes. In-depth information is obtained about the exergy (maximum work a system can make, exergy losses and destruction at the power plant and its components. Thus the performance of the power plant may be predicted with reasonable accuracy and better understanding is gained for the physical process to be used in improving the performance of the power plant. The results of the exergy analysis show that total exergy production rate and exergy efficiency of the GPP are 21 MW and 14.52%, respectively, after removing parasitic loads. The highest amount of exergy destruction occurs, respectively, in condenser 2, vaporizer HH2, condenser 1, pumps 1 and 2 as components requiring priority performance improvement. To maximize the system exergy efficiency, the artificial bee colony (ABC is applied to the model that simulates the actual GPP. Under all the optimization conditions, the maximum exergy efficiency for the GPP and its components is obtained. Two of these conditions such as Case 4 related to the turbine and Case 12 related to the condenser have the best performance. As a result, the ABC optimization method provides better quality information than exergy analysis. Based on the guidance of this study, the performance of power plants based on geothermal energy and other energy resources may be improved.

  19. Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

    Science.gov (United States)

    2014-01-01

    Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

  20. Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm.

    Science.gov (United States)

    Li, Bai; Lin, Mu; Liu, Qiao; Li, Ya; Zhou, Changjun

    2015-10-01

    Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques.

  1. Optimization of travel salesman problem using the ant colony system and Greedy search; Optimizacion del problema del agente viajero usando el sistema de colonia de hormigas y busqueda Greedy

    Energy Technology Data Exchange (ETDEWEB)

    Esquivel E, J.; Ordonez A, A. [Universidad Autonoma del Estado de Mexico, Facultad de Ingenieria, Cerro de Coatepec s/n, Toluca, Estado de Mexico (Mexico); Ortiz S, J. J. [Departamento de Sistemas Nucleares, ININ, Carretera Mexico-Toluca s/n, Ocoyoacac 52750, Estado de Mexico (Mexico)

    2008-07-01

    In this paper we present some results obtained during the development of optimization systems that can be used to design refueling and patterns of control rods in a BWR. These systems use ant colonies and Greedy search. The first phase of this project is to be familiar with these optimization techniques applied to the problem of travel salesman problem (TSP). The utility of TSP study is that, like the refueling design and pattern design of control rods are problems of combinative optimization. Even, the similarity with the problem of the refueling design is remarkable. It is presented some results for the TSP with the 32 state capitals of Mexico country. (Author)

  2. A methodology for obtaining the control rods patterns in a BWR using systems based on ants colonies; Una metodologia para obtener los patrones de barras de control en un BWR usando sistemas basados en colonias de hormigas

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz S, J.J. [Depto. de Sistemas Nucleares, ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico); Requena R, I. [Universidad de Granada, 18071 Granada (Spain)]. e-mail: jjortiz@nuclear.inin.mx

    2003-07-01

    In this work the AZCATL-PBC system based on a technique of ants colonies for the search of control rods patterns of those reactors of the Nuclear Power station of Laguna Verde (CNLV) is presented. The technique was applied to a transition cycle and one of balance. For both cycles they were compared the k{sub ef} values obtained with a Haling calculation and the control rods pattern proposed by AZCATL-PBC for a burnt one fixed. It was found that the methodology is able to extend the length of the cycle with respect to the Haling prediction, maintaining sure to the reactor. (Author)

  3. Energy Efficient Routing in Wireless Sensor Networks based on Ant ...

    African Journals Online (AJOL)

    PROF. O. E. OSUAGWU

    2013-09-01

    Sep 1, 2013 ... Ant Colony Optimization, a swarm intelligence based optimization technique, has been successfully used in network routing. In this paper, we introduce a heuristic way to reduce energy consumption in WSNs routing process using Ant Colony Optimization. We introduce three Ant Colony Optimization ...

  4. Protein Tertiary Structure Prediction Based on Main Chain Angle Using a Hybrid Bees Colony Optimization Algorithm

    Science.gov (United States)

    Mahmood, Zakaria N.; Mahmuddin, Massudi; Mahmood, Mohammed Nooraldeen

    Encoding proteins of amino acid sequence to predict classified into their respective families and subfamilies is important research area. However for a given protein, knowing the exact action whether hormonal, enzymatic, transmembranal or nuclear receptors does not depend solely on amino acid sequence but on the way the amino acid thread folds as well. This study provides a prototype system that able to predict a protein tertiary structure. Several methods are used to develop and evaluate the system to produce better accuracy in protein 3D structure prediction. The Bees Optimization algorithm which inspired from the honey bees food foraging method, is used in the searching phase. In this study, the experiment is conducted on short sequence proteins that have been used by the previous researches using well-known tools. The proposed approach shows a promising result.

  5. From so simple a beginning: Enzymatic innovation in fungus-growing ants involved a transition from individual symbiont selection to colony-level selection

    DEFF Research Database (Denmark)

    de Fine Licht, Henrik Hjarvard; Schiøtt, Morten; Boomsma, Jacobus Jan

    of the partner species. Here we document such a sequence that was connected to a major evolutionary transition in the fungus-growing ants, when the ancestor of the derived leaf-cutting ants shifted from a diet of dry vegetative material to the almost exclusive use of freshly cut leaves. This shift generated...... visible adaptations in the host ants, such as increased worker dimorphism allowing large workers to cut fresh leaves, but comparative studies of the specific fungal adaptations that accompanied the transition have not been done. Here we report the first large comparative data set on enzymatic fungus...... garden profiles and focus on one of these enzymes, a laccase that is believed to oxidize phenols in defensive secondary plant compounds. We show that this laccase is exclusively found in the gardens of leaf-cutting ants where it can be inferred to have arisen by selection at the individual level when...

  6. Strict monandry in the ponerine army ant genus Simopelta suggests that colony size and complexity drive mating system evolution in social insects

    DEFF Research Database (Denmark)

    Kronauer, Daniel J C; O'Donnell, Sean; Boomsma, Jacobus J

    2011-01-01

    Altruism in social insects has evolved between closely related full-siblings. It is therefore of considerable interest why some groups have secondarily evolved low within-colony relatedness, which in turn affects the relatedness incentives of within-colony cooperation and conflict. The highest qu...

  7. KANTS: a stigmergic ant algorithm for cluster analysis and swarm art.

    Science.gov (United States)

    Fernandes, Carlos M; Mora, Antonio M; Merelo, Juan J; Rosa, Agostinho C

    2014-06-01

    KANTS is a swarm intelligence clustering algorithm inspired by the behavior of social insects. It uses stigmergy as a strategy for clustering large datasets and, as a result, displays a typical behavior of complex systems: self-organization and global patterns emerging from the local interaction of simple units. This paper introduces a simplified version of KANTS and describes recent experiments with the algorithm in the context of a contemporary artistic and scientific trend called swarm art, a type of generative art in which swarm intelligence systems are used to create artwork or ornamental objects. KANTS is used here for generating color drawings from the input data that represent real-world phenomena, such as electroencephalogram sleep data. However, the main proposal of this paper is an art project based on well-known abstract paintings, from which the chromatic values are extracted and used as input. Colors and shapes are therefore reorganized by KANTS, which generates its own interpretation of the original artworks. The project won the 2012 Evolutionary Art, Design, and Creativity Competition.

  8. a new meta-heuristic optimization algorithm

    Indian Academy of Sciences (India)

    N Archana

    ACO is inspired by food search of an ant colony, ABC is based on bees finding flowers with adequate nectar, ... algorithms have some parameters that are set by the user, which alter their behaviour to a great extent. ..... obtained are thus the result of proper choice of location and sizing of UPFC and STATCOM devices in the ...

  9. Sick ants become unsociable

    DEFF Research Database (Denmark)

    Bos, Nicky Peter Maria; Lefevre, T.; Jensen, A.B.

    2012-01-01

    Parasites represent a severe threat to social insects, which form high-density colonies of related individuals, and selection should favour host traits that reduce infection risk. Here, using a carpenter ant (Camponotus aethiops) and a generalist insect pathogenic fungus (Metarhizium brunneum), we...... show that infected ants radically change their behaviour over time to reduce the risk of colony infection. Infected individuals (i) performed less social interactions than their uninfected counterparts, (ii) did not interact with brood anymore and (iii) spent most of their time outside the nest from...... day 3 post-infection until death. Furthermore, infected ants displayed an increased aggressiveness towards non-nestmates. Finally, infected ants did not alter their cuticular chemical profile, suggesting that infected individuals do not signal their physiological status to nestmates. Our results...

  10. A novel approach to speckle noise filtering based on Artificial Bee Colony algorithm: an ultrasound image application.

    Science.gov (United States)

    Latifoğlu, Fatma

    2013-09-01

    In this study a novel approach based on 2D FIR filters is presented for denoising digital images. In this approach the filter coefficients of 2D FIR filters were optimized using the Artificial Bee Colony (ABC) algorithm. To obtain the best filter design, the filter coefficients were tested with different numbers (3×3, 5×5, 7×7, 11×11) and connection types (cascade and parallel) during optimization. First, the speckle noise with variances of 1, 0.6, 0.8 and 0.2 respectively was added to the synthetic test image. Later, these noisy images were denoised with both the proposed approach and other well-known filter types such as Gaussian, mean and average filters. For image quality determination metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) were used. Even in the case of noise having maximum variance (the most noisy), the proposed approach performed better than other filtering methods did on the noisy test images. In addition to test images, speckle noise with a variance of 1 was added to a fetal ultrasound image, and this noisy image was denoised with very high PSNR and SNR values. The performance of the proposed approach was also tested on several clinical ultrasound images such as those obtained from ovarian, abdomen and liver tissues. The results of this study showed that the 2D FIR filters designed based on ABC optimization can eliminate speckle noise quite well on noise added test images and intrinsically noisy ultrasound images. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  11. The effect of queen and worker adoption on weaver ant (Oecophylla smaragdina) queen fecundity

    DEFF Research Database (Denmark)

    Offenberg, Joachim; Peng, Renkang; Nielsen, Mogens Gissel

    2012-01-01

    Incipient ant colonies are often under fierce competition, making fast growth crucial for survival. To increase production, colonies can adopt multiple queens (pleometrosis), fuse with other colonies or rob brood from neighboring colonies. However, different adoption strategies might have different...

  12. Controlling‏ ‏the Balance of Exploration and ‎Exploitation in ACO Algorithm

    Directory of Open Access Journals (Sweden)

    Ayad ‎ Mohammed Jabbar

    2018-02-01

    Full Text Available Ant colony optimization is a meta-heuristic algorithm inspired by the foraging behavior of real ant colony. The algorithm is a population-based solution employed in different optimization problems such as classification, image processing, clustering, and so on. This paper sheds the light on the side of improving the results of traveling salesman problem produced by the algorithm. The key success that produces the valuable results is due to the two important components of exploration and exploitation. Balancing both components is the foundation of controlling search within the ACO. This paper proposes to modify the main probabilistic method to overcome the drawbacks of the exploration problem and produces global optimal results in high dimensional space. Experiments on six variant of ant colony optimization indicate that the proposed work produces high-quality results in terms of shortest route

  13. A cellular automata model for ant trails

    Indian Academy of Sciences (India)

    It is easy to comprehend the population biology of social insect colonies [11] using the basic principles which affect the formation of the ant trails. ..... [19] M G Deborah, Ant encounters interaction networks and colony behavior (Princeton Univer- sity Press, Princeton, New Jersey, 2010). [20] K Nishinari, D Chowdhury and A ...

  14. Immune defense in leaf-cutting ants

    DEFF Research Database (Denmark)

    Armitage, Sophie A O; Broch, Jens F; Marín, Hermogenes Fernández

    2011-01-01

    -fostering experiment designed to address the influences of genotype and social rearing environment upon individual and social immune defenses. We used a multiply mating leaf-cutting ant, enabling us to test for patriline effects within a colony, as well as cross-colony matriline effects. The worker's father influenced...... social defense, a Pseudonocardia bacteria that helps to control pathogens in the ants' fungus garden, showed a significant colony of origin by rearing environment interaction, whereby ants that acquired the bacteria of a foster colony obtained a less abundant cover of bacteria: one explanation...

  15. Evaluation of the performance of different firefly algorithms to the ...

    African Journals Online (AJOL)

    Swarm Optimization (PSO), Ant Colony optimization (ACO), and Firefly Algorithm (FFA) (Moustafa et al., 2016). The FFA is a developing optimization technique that is simple with a great ability to converge to optimum solutions faster than other intelligent methods (Subramanian and Thanushkodi, 2013; Younes, 2013).

  16. Algorithms bio-inspired for the pattern obtention of control bars in BWR reactors

    International Nuclear Information System (INIS)

    Ortiz, J.J.; Perusquia, R.; Montes, J.L.

    2003-01-01

    In this work methods based on Genetic Algorithms and Systems based on ant colonies for the obtention of the patterns of control bars of an equilibrium cycle of 18 months for the Laguna Verde nuclear power station are presented. A comparison of obtained results with the methods and with those of design of such equilibrium cycle is presented. As consequence of the study, it was found that the algorithm based on the ant colonies reached to diminish the coast down period (decrease of power at the end of the cycle) in five and half days with respect to the original design what represents an annual saving of $US 100,000. (Author)

  17. Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

    Science.gov (United States)

    Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

    2016-01-01

    Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

  18. A comparison of genetic algorithm and artificial bee colony approaches in solving blocking hybrid flowshop scheduling problem with sequence dependent setup/changeover times

    Directory of Open Access Journals (Sweden)

    Pongpan Nakkaew

    2016-06-01

    Full Text Available In manufacturing process where efficiency is crucial in order to remain competitive, flowshop is a common configuration in which machines are arranged in series and products are produced through the stages one by one. In certain production processes, the machines are frequently configured in the way that each production stage may contain multiple processing units in parallel or hybrid. Moreover, along with precedent conditions, the sequence dependent setup times may exist. Finally, in case there is no buffer, a machine is said to be blocked if the next stage to handle its output is being occupied. Such NP-Hard problem, referred as Blocking Hybrid Flowshop Scheduling Problem with Sequence Dependent Setup/Changeover Times, is usually not possible to find the best exact solution to satisfy optimization objectives such as minimization of the overall production time. Thus, it is usually solved by approximate algorithms such as metaheuristics. In this paper, we investigate comparatively the effectiveness of the two approaches: a Genetic Algorithm (GA and an Artificial Bee Colony (ABC algorithm. GA is inspired by the process of natural selection. ABC, in the same manner, resembles the way types of bees perform specific functions and work collectively to find their foods by means of division of labor. Additionally, we apply an algorithm to improve the GA and ABC algorithms so that they can take advantage of parallel processing resources of modern multiple core processors while eliminate the need for screening the optimal parameters of both algorithms in advance.

  19. The logic of hypersocial colonies

    DEFF Research Database (Denmark)

    Pedersen, Jes Søe

    2012-01-01

    It is no wonder that we are transfixed with fascination when we stand in the midst of an ocean of flowing ants within a single extensive society of one of the invasive species. Normal terms do not fit anymore: this is not just a colony, but a “supercolony.” The iconic supercolonial species...... is the Argentine ant, infamous as a pest and now very well studied, all the way from having its genome sequenced to its global distribution mapped. As the Argentine ant can be the key to understanding other supercolonial and/or invasive ants, it is very timely that Moffett's review (2012) focuses on how we...

  20. Chemically armed mercenary ants protect fungus-farming societies

    DEFF Research Database (Denmark)

    Adams, Rachelle Martha Marie; Liberti, Joanito; Illum, Anders A.

    2013-01-01

    The ants are extraordinary in having evolved many lineages that exploit closely related ant societies as social parasites, but social parasitism by distantly related ants is rare. Here we document the interaction dynamics among a Sericomyrmex fungus-growing ant host, a permanently associated...... parasitic guest ant of the genus Megalomyrmex, and a raiding agro-predator of the genus Gnamptogenys. We show experimentally that the guest ants protect their host colonies against agro-predator raids using alkaloid venom that is much more potent than the biting defenses of the host ants. Relatively few...... guest ants are sufficient to kill raiders that invariably exterminate host nests without a cohabiting guest ant colony. We also show that the odor of guest ants discourages raider scouts from recruiting nestmates to host colonies. Our results imply that Sericomyrmex fungus-growers obtain a net benefit...

  1. Honey Ants.

    Science.gov (United States)

    Conway, John R.

    1984-01-01

    Provides background information on honey ants. These ants are found in dry or desert regions of North America, Africa, and Australia. Also provides a list of activities using local species of ants. (JN)

  2. An efficient algorithm for function optimization: modified stem cells algorithm

    Science.gov (United States)

    Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad

    2013-03-01

    In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

  3. Stealthy invaders: the biology of Cardiocondyla tramp ants

    DEFF Research Database (Denmark)

    Heinze, J.; Cremer, Sylvia; Eckl, N.

    2006-01-01

    Many invasive ant species, such as the Argentine ant or the red imported fire ant, have huge colonies with thousands of mass-foraging workers, which quickly monopolise resources and therefore represent a considerable threat to the native ant fauna. Cardiocondyla obscurior and several other species...

  4. Introduced fire ants can exclude native ants from critical mutualist-provided resources.

    Science.gov (United States)

    Wilder, Shawn M; Barnum, Thomas R; Holway, David A; Suarez, Andrew V; Eubanks, Micky D

    2013-05-01

    Animals frequently experience resource imbalances in nature. For ants, one resource that may be particularly valuable for both introduced and native species is high-carbohydrate honeydew from hemipteran mutualists. We conducted field and laboratory experiments: (1) to test if red imported fire ants (Solenopsis invicta) competed with native ants for access to mutualisms with aphids, and (2) to quantify the effects of aphid honeydew presence or absence on colony growth of native ants. We focused on native dolichoderine ants (Formicidae, Dolichoderinae) because they are abundant ants that have omnivorous diets that frequently include mutualist-provided carbohydrates. At two sites in the southeastern US, native dolichoderine ants were far less frequent, and fire ants more frequent, at carbohydrate baits than would be expected based on their frequency in pitfall traps. A field experiment confirmed that a native ant species, Dorymyrmex bureni, was only found tending aphids when populations of S. invicta were suppressed. In the laboratory, colonies of native dolichoderine ants with access to both honeydew and insect prey had twice as many workers and over twice as much brood compared to colonies fed only ad libitum insect prey. Our results provide the first experimental evidence that introduced ants compete for access to mutualist-provided carbohydrates with native ants and that these carbohydrates represent critical resources for both introduced and native ants. These results challenge traditional paradigms of arthropod and ant nutrition and contribute to growing evidence of the importance of nutrition in mediating ecological interactions.

  5. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  6. Del hogar a los juzgados: reclamos familiares ante la Real Audiencia de Santafé a finales del período colonial (1800-1809.

    Directory of Open Access Journals (Sweden)

    Catalina Villegas del Castillo.

    2006-01-01

    Full Text Available The law is an important source for the historic reconstruction of the family. Colombian historiography has tried to develop this kind of analysis under the premise that it is possible to identify the morality, customs and dominant institutions of the period in question, as well interpret the changes and transformations of historic processes, from the reigning norms of the period studied. These studies have brought to light the situation of women, mothers and wives in a country marked by a strong patriarchal tradition. This article, by contrast, studies the relationship between the family and the State through an examination of court cases. These sources complement the purely formal analysis, in that they allow us to identity how mothers, spouses and children used the dominant religious, moral, political and legal norms in order to defend their interests within the legal process. The court cases also helped establish the dominant models of women and men that judges of the era appealed to and defended in their judicial decisions. This article is based on an examination of lawsuits regarding food claims and opposition-to-marriage trials contained in the collection of Asuntos Civiles (Civil Matters, in the Colonial section of the Archivo General de la Nación.

  7. A Knowledge-Informed and Pareto-Based Artificial Bee Colony Optimization Algorithm for Multi-Objective Land-Use Allocation

    Directory of Open Access Journals (Sweden)

    Lina Yang

    2018-02-01

    Full Text Available Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front reflecting different tradeoffs in several objectives. However, obtaining a Pareto front is a challenging task, and the Pareto front obtained by state-of-the-art algorithms is still not sufficient. To achieve better Pareto solutions, taking the grid-representative land-use allocation problem with two objectives as an example, an artificial bee colony optimization algorithm for multi-objective land-use allocation (ABC-MOLA is proposed. In this algorithm, the traditional ABC’s search direction guiding scheme and solution maintaining process are modified. In addition, a knowledge-informed neighborhood search strategy, which utilizes the auxiliary knowledge of natural geography and spatial structures to facilitate the neighborhood spatial search around each solution, is developed to further improve the Pareto front’s quality. A series of comparison experiments (a simulated experiment with small data volume and a real-world data experiment for a large area shows that all the Pareto fronts obtained by ABC-MOLA totally dominate the Pareto fronts by other algorithms, which demonstrates ABC-MOLA’s effectiveness in achieving Pareto fronts of high quality.

  8. Fungal Adaptations to Mutualistic Life with Ants

    DEFF Research Database (Denmark)

    Kooij, Pepijn Wilhelmus

    Fungus-growing ants (Attini) feed off a fungus they cultivate in a mutualistic symbiosis in underground chambers by providing it substrate they collect outside the colony. The tribe of Attine ants ranges from small colonies of the paleo- and basal Attine species with a few hundred workers...... that forage on crude substrates such as insect frass and dry plant material, to large colonies of the leaf-cutting ants with several thousands to several million workers that provide live plant material to their fungus gardens. Leaf-cutting ants are the dominant herbivores of the Neo-tropics, and have a major...... contribution to cycling of nitrogen and phosphorus in their direct environment and are, furthermore, considered pest species as they have a large impact on human agriculture. These factors make leaf-cutting ants an ideal study subject to better understand the mechanisms that make this mutualistic symbiosis so...

  9. Microsatellite Primers for Fungus-Growing Ants

    DEFF Research Database (Denmark)

    Villesen Fredsted, Palle; Gertsch, Pia J.; Boomsma, Jacobus Jan (Koos)

    2002-01-01

    We isolated five polymorphic microsatellite loci from a library of two thousand recombinant clones of two fungus-growing ant species, Cyphomyrmex longiscapus and Trachymyrmex cf. zeteki. Amplification and heterozygosity were tested in five species of higher attine ants using both the newly...... developed primers and earlier published primers that were developed for fungus-growing ants. A total of 20 variable microsatellite loci, developed for six different species of fungus-growing ants, are now available for studying the population genetics and colony kin-structure of these ants....

  10. Microsatellite primers for fungus-growing ants

    DEFF Research Database (Denmark)

    Villesen, Palle; Gertsch, P J; Boomsma, JJ

    2002-01-01

    We isolated five polymorphic microsatellite loci from a library of two thousand recombinant clones of two fungus-growing ant species, Cyphomyrmex longiscapus and Trachymyrmex cf. zeteki. Amplification and heterozygosity were tested in five species of higher attine ants using both the newly...... developed primers and earlier published primers that were developed for fungus-growing ants. A total of 20 variable microsatellite loci, developed for six different species of fungus-growing ants, are now available for studying the population genetics and colony kin-structure of these ants....

  11. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    Science.gov (United States)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  12. Non-destructive estimation of Oecophylla smaragdina colony biomass

    DEFF Research Database (Denmark)

    Pinkalski, Christian Alexander Stidsen; Offenberg, Joachim; Jensen, Karl-Martin Vagn

    In most ecosystems, ants are a dominant part of the arthropod community. However, understanding of their importance has been hampered by limited availability of data on ant abundance. We developed a model to estimate the size (biomass and number of workers) of Oecophylla smaragdina colonies...... in mango plantations in Darwin, Australia. The total nest volume of O. smaragdina colonies in a tree was related to the activity of the ants (R2=0.85), estimated as the density of ant trails in the tree. Subsequently, the relation between nest volume and ant biomass (R2=0.70) was added to enable...... a prediction of ant biomass directly from ant activity. With this combined regression the ant biomass in a tree equaled 244.5 g fresh mass*ant activity. Similarly, the number of workers in trees was estimated using the relationship between nest volume and worker numbers (R2=0.84). Based on the model, five O...

  13. Ant system for reliability optimization of a series system with multiple-choice and budget constraints

    International Nuclear Information System (INIS)

    Nahas, Nabil; Nourelfath, Mustapha

    2005-01-01

    Many researchers have shown that insect colonies behavior can be seen as a natural model of collective problem solving. The analogy between the way ants look for food and combinatorial optimization problems has given rise to a new computational paradigm, which is called ant system. This paper presents an application of ant system in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. This problem is solved by developing and demonstrating a problem-specific ant system algorithm. In this algorithm, solutions of the reliability optimization problem are repeatedly constructed by considering the trace factor and the desirability factor. A local search is used to improve the quality of the solutions obtained by each ant. A penalty factor is introduced to deal with the budget constraint. Simulations have shown that the proposed ant system is efficient with respect to the quality of solutions and the computing time

  14. A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

    Science.gov (United States)

    Parmaksızoğlu, Selami; Alçı, Mustafa

    2011-01-01

    Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

  15. A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

    Science.gov (United States)

    Parmaksızoğlu, Selami; Alçı, Mustafa

    2011-01-01

    Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

  16. Fungal Adaptations to Mutualistic Life with Ants

    DEFF Research Database (Denmark)

    Kooij, Pepijn Wilhelmus

    that forage on crude substrates such as insect frass and dry plant material, to large colonies of the leaf-cutting ants with several thousands to several million workers that provide live plant material to their fungus gardens. Leaf-cutting ants are the dominant herbivores of the Neo-tropics, and have a major...

  17. Identification of related multilingual documents using ant clustering algorithms Identificación de documentos multilingües relacionados mediante algoritmos de clustering de hormigas

    Directory of Open Access Journals (Sweden)

    Ángel Cobo

    2011-12-01

    Full Text Available This paper presents a document representation strategy and a bio-inspired algorithm to cluster multilingual collections of documents in the field of economics and business. The proposed approach allows the user to identify groups of related economics documents written in Spanish and English using techniques inspired on clustering and sorting behaviours observed in some types of ants. In order to obtain a language independent vector representation of each document two multilingual resources are used: an economic glossary and a thesaurus. Each document is represented using four feature vectors: words, proper names, economic terms in the glossary and thesaurus descriptors. The proper name identification, word extraction and lemmatization are performed using specific tools. The tf-idf scheme is used to measure the importance of each feature in the document, and a convex linear combination of angular separations between feature vectors is used as similarity measure of documents. The paper shows experimental results of the application of the proposed algorithm in a Spanish-English corpus of research papers in economics and management areas. The results demonstrate the usefulness and effectiveness of the ant clustering algorithm and the proposed representation scheme.Este artículo presenta una estrategia de representación documental y un algoritmo bioinspirado para realizar procesos de agrupamiento en colecciones multilingües de documentos en las áreas de la economía y la empresa. El enfoque propuesto permite al usuario identificar grupos de documentos económicos relacionados escritos en español o inglés usando técnicas inspiradas en comportamientos de organización y agrupamiento de objetos observados en algunos tipos de hormigas. Para conseguir una representación vectorial de cada documento independiente del idioma, se han utilizado dos recursos lingüísticos: un glosario económico y un tesauro. Cada documento es representado usando

  18. Ant Foraging Behavior for Job Shop Problem

    Directory of Open Access Journals (Sweden)

    Mahad Diyana Abdul

    2016-01-01

    Full Text Available Ant Colony Optimization (ACO is a new algorithm approach, inspired by the foraging behavior of real ants. It has frequently been applied to many optimization problems and one such problem is in solving the job shop problem (JSP. The JSP is a finite set of jobs processed on a finite set of machine where once a job initiates processing on a given machine, it must complete processing and uninterrupted. In solving the Job Shop Scheduling problem, the process is measure by the amount of time required in completing a job known as a makespan and minimizing the makespan is the main objective of this study. In this paper, we developed an ACO algorithm to minimize the makespan. A real set of problems from a metal company in Johor bahru, producing 20 parts with jobs involving the process of clinching, tapping and power press respectively. The result from this study shows that the proposed ACO heuristics managed to produce a god result in a short time.

  19. Multi-criteria ACO-based Algorithm for Ship’s Trajectory Planning

    Directory of Open Access Journals (Sweden)

    Agnieszka Lazarowska

    2017-03-01

    Full Text Available The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a multi-criteria optimization task. The criteria taken into account during problem solving are: path safety, path length, the International Regulations for Preventing Collisions at Sea (COLREGs compliance and path smoothness. The paper includes the description of the new multi-criteria ACO-based algorithm along with the presentation and discussion of simulation tests results.

  20. Emergency networking: famine relief in ant colonies

    NARCIS (Netherlands)

    Sendova-Franks, A.B.; Hayward, R.; Wulf, B.; Klimek, T.; James, R.; Planque, R.; Britton, N.F.; Franks, N.R.

    2009-01-01

    Resource distribution is fundamental to social organization, but it poses a dilemma. How to facilitate the spread of useful resources but restrict harmful substances? This dilemma reaches a zenith in famine relief. Survival depends on distributing food fast but that could increase vulnerability to

  1. Algorithms bio-inspired for the pattern obtention of control bars in BWR reactors; Algoritmos bio-inspirados para la obtencion de patrones de barras de control en reactores BWR

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz, J.J.; Perusquia, R.; Montes, J.L. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)

    2003-07-01

    In this work methods based on Genetic Algorithms and Systems based on ant colonies for the obtention of the patterns of control bars of an equilibrium cycle of 18 months for the Laguna Verde nuclear power station are presented. A comparison of obtained results with the methods and with those of design of such equilibrium cycle is presented. As consequence of the study, it was found that the algorithm based on the ant colonies reached to diminish the coast down period (decrease of power at the end of the cycle) in five and half days with respect to the original design what represents an annual saving of $US 100,000. (Author)

  2. Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

    Science.gov (United States)

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-10-22

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

  3. On the application of artificial bee colony (ABC algorithm for optimization of well placements in fractured reservoirs; efficiency comparison with the particle swarm optimization (PSO methodology

    Directory of Open Access Journals (Sweden)

    Behzad Nozohour-leilabady

    2016-03-01

    Full Text Available The application of a recent optimization technique, the artificial bee colony (ABC, was investigated in the context of finding the optimal well locations. The ABC performance was compared with the corresponding results from the particle swarm optimization (PSO algorithm, under essentially similar conditions. Treatment of out-of-boundary solution vectors was accomplished via the Periodic boundary condition (PBC, which presumably accelerates convergence towards the global optimum. Stochastic searches were initiated from several random staring points, to minimize starting-point dependency in the established results. The optimizations were aimed at maximizing the Net Present Value (NPV objective function over the considered oilfield production durations. To deal with the issue of reservoir heterogeneity, random permeability was applied via normal/uniform distribution functions. In addition, the issue of increased number of optimization parameters was address, by considering scenarios with multiple injector and producer wells, and cases with deviated wells in a real reservoir model. The typical results prove ABC to excel PSO (in the cases studied after relatively short optimization cycles, indicating the great premise of ABC methodology to be used for well-optimization purposes.

  4. A Hybrid Algorithm Based on ACO and PSO for Capacitated Vehicle Routing Problems

    Directory of Open Access Journals (Sweden)

    Yucheng Kao

    2012-01-01

    Full Text Available The vehicle routing problem (VRP is a well-known combinatorial optimization problem. It has been studied for several decades because finding effective vehicle routes is an important issue of logistic management. This paper proposes a new hybrid algorithm based on two main swarm intelligence (SI approaches, ant colony optimization (ACO and particle swarm optimization (PSO, for solving capacitated vehicle routing problems (CVRPs. In the proposed algorithm, each artificial ant, like a particle in PSO, is allowed to memorize the best solution ever found. After solution construction, only elite ants can update pheromone according to their own best-so-far solutions. Moreover, a pheromone disturbance method is embedded into the ACO framework to overcome the problem of pheromone stagnation. Two sets of benchmark problems were selected to test the performance of the proposed algorithm. The computational results show that the proposed algorithm performs well in comparison with existing swarm intelligence approaches.

  5. Kin-informative recognition cues in ants

    DEFF Research Database (Denmark)

    Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A

    2011-01-01

    behaviour is thought to be rare in one of the classic examples of cooperation--social insect colonies--because the colony-level costs of individual selfishness select against cues that would allow workers to recognize their closest relatives. In accord with this, previous studies of wasps and ants have...... found little or no kin information in recognition cues. Here, we test the hypothesis that social insects do not have kin-informative recognition cues by investigating the recognition cues and relatedness of workers from four colonies of the ant Acromyrmex octospinosus. Contrary to the theoretical...... prediction, we show that the cuticular hydrocarbons of ant workers in all four colonies are informative enough to allow full-sisters to be distinguished from half-sisters with a high accuracy. These results contradict the hypothesis of non-heritable recognition cues and suggest that there is more potential...

  6. Discrimination Behavior in the Supercolonial Pharaoh Ant

    DEFF Research Database (Denmark)

    Pontieri, Luigi

    the discrimination behavior of the invasive pharaoh ant (Monomorium pharaonis) as a model for other invasive and supercolonial ant species. The pharaoh ant is one of the few ant species that can be reared in the laboratory for many generations. Furthermore, the possibility to do controlled crosses of colonies...... provides the unique opportunity to establish colonies of different genetic composition. These traits make this species a suitable study subject to set up behavioral experiments that aim to investigate which factors, and to which extent, might influence the inter- and intraspecific discrimination abilities...... other compounds. We also developed a new method for centroid calculation that increased the power of the analysis and can therefore be used in future studies that aim to identify nestmate recognition cues in other species. In the fourth chapter I investigated the nest site preference of pharaoh ant...

  7. Beyond ANT

    DEFF Research Database (Denmark)

    Jansen, Till

    2017-01-01

    Actor-Network-Theory (ANT) offers an ‘infra-language’ of the social that allows one to trace social relations very dynamically, while at the same time dissolving human agency, thus providing a flat and de-centred way into sociology. However, ANT struggles with its theoretical design that may lead......, it offers an ‘infra-language’ of reflexive relations while maintaining ANT’s de-centred approach. This would enable us to conceptualize actor-networks as non-homogeneous, dynamic and connecting different societal rationales while maintaining the main strengths of ANT.......Actor-Network-Theory (ANT) offers an ‘infra-language’ of the social that allows one to trace social relations very dynamically, while at the same time dissolving human agency, thus providing a flat and de-centred way into sociology. However, ANT struggles with its theoretical design that may lead...

  8. The effect carbohydrate consumption on Argentine ants' nutritional ecology

    OpenAIRE

    Chou, Cheng T.

    2009-01-01

    As a result of accidental introduction, the invasive Argentine ant, Linepithema humile, has successfully invaded many parts of the world including the California coast. Argentine ants are extraordinarily effective in displacing native ants. This study aims to link animal behavior and growth to resource consumption. We examined how different diets affect Argentine ant behavior. We hypothesized that having a diet composed of both carbohydrate and protein may increase colony size and activity le...

  9. Algorithms

    Indian Academy of Sciences (India)

    have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming language Is called a program. From activities 1-3, we can observe that: • Each activity is a command.

  10. Signals can trump rewards in attracting seed-dispersing ants.

    Directory of Open Access Journals (Sweden)

    Kyle M Turner

    Full Text Available Both rewards and signals are important in mutualisms. In myrmecochory, or seed dispersal by ants, the benefits to plants are relatively well studied, but less is known about why ants pick up and move seeds. We examined seed dispersal by the ant Aphaenogaster rudis of four co-occurring species of plants, and tested whether morphology, chemical signaling, or the nutritional quality of fatty seed appendages called elaiosomes influenced dispersal rates. In removal trials, ants quickly collected diaspores (seeds plus elaiosomes of Asarum canadense, Trillium grandiflorum, and Sanguinaria canadensis, but largely neglected those of T. erectum. This discrepancy was not explained by differences in the bulk cost-benefit ratio, as assessed by the ratio of seed to elaiosome mass. We also provisioned colonies with diaspores from one of these four plant species or no diaspores as a control. Colonies performed best when fed S. canadensis diaspores, worst when fed T. grandiflorum, and intermediately when fed A. canadense, T. erectum, or no diaspores. Thus, the nutritional rewards in elaiosomes affected colony performance, but did not completely predict seed removal. Instead, high levels of oleic acid in T. grandiflorum elaiosomes may explain why ants disperse these diaspores even though they reduce ant colony performance. We show for the first time that different elaiosome-bearing plants provide rewards of different quality to ant colonies, but also that ants appear unable to accurately assess reward quality when encountering seeds. Instead, we suggest that signals can trump rewards as attractants of ants to seeds.

  11. Fire ants

    Science.gov (United States)

    ... 222-1222) from anywhere in the United States. Poisonous Ingredient Fire ant venom contains a chemical called ... Elsevier Saunders; 2013:chap 140. Otten EJ. Venomous animal injuries. In: Walls RM, Hockberger RS, Gausche-Hill ...

  12. Colonial Institutions

    DEFF Research Database (Denmark)

    McAtackney, Laura; Palmer, Russell

    2016-01-01

    Archaeologically based explorations of colonialism or institutions are common case-studies in global historical archaeology, but the “colonial institution”—the role of institutions as operatives of colonialism—has often been neglected. In this thematic edition we argue that in order to fully...... understand the interconnected, global world one must explicitly dissect the colonial institution as an entwined, dual manifestation that is central to understanding both power and power relations in the modern world. Following Ann Laura Stoler, we have selected case studies from the Australia, Europe, UK...... and the USA which reveal that the study of colonial institutions should not be limited to the functional life of these institutions—or solely those that take the form of monumental architecture—but should include the long shadow of “imperial debris” (Stoler 2008) and immaterial institutions....

  13. Disease dynamics in a specialized parasite of ant societies

    DEFF Research Database (Denmark)

    Andersen, Sandra Breum; Ferrari, Matthew; Evans, Harry C.

    2012-01-01

    Coevolution between ant colonies and their rare specialized parasites are intriguing, because lethal infections of workers may correspond to tolerable chronic diseases of colonies, but the parasite adaptations that allow stable coexistence with ants are virtually unknown. We explore the trade......-offs experienced by Ophiocordyceps parasites manipulating ants into dying in nearby graveyards. We used field data from Brazil and Thailand to parameterize and fit a model for the growth rate of graveyards. We show that parasite pressure is much lower than the abundance of ant cadavers suggests...

  14. Tamaño y composición de la colonia de tres especies de hormigas del género Pogonomyrmex (Hymenoptera: Formicidae en la porción central del desierto del Monte, Argentina Colony size and composition in three Pogonomyrmex ant species (Hymenoptera: Formicidae in the central Monte desert, Argentina

    Directory of Open Access Journals (Sweden)

    Beatriz E. Nobua Behrmann

    2010-06-01

    Full Text Available El tamaño de la colonia es un atributo fundamental en la biología de las hormigas ya que está asociado a características ecológicamente relevantes, como sus estrategias de alimentación. Mientras que el tamaño de la colonia de varias especies de hormigas granívoras del género Pogonomyrmex de América del Norte se ha estudiado en detalle, no existe tal información para las especies de América del Sur. En este trabajo, se determinó el tamaño y la composición de la colonia y se describió la estructura del nido de tres especies de Pogonomyrmex que habitan la porción central del desierto del Monte en Argentina: P. mendozanus Cuezzo & Claver, P. inermis Forel y P. rastratus Mayr. Para ello, se excavaron dos nidos de cada especie y se recolectaron todos los individuos encontrados. Las tres especies tienen colonias pequeñas, compuestas por 300-1.100 individuos, de los cuales aproximadamente el 70% son obreras adultas. La estructura de sus nidos es relativamente simple, similar a la de la mayoría de las especies norteamericanas estudiadas, pero con un menor desarrollo en profundidad y un número menor de cámaras; probablemente se deba al menor número de obreras que poseen. Estas características (colonias pequeñas y nidos poco desarrollados son consideradas típicas para las especies del género Pogonomyrmex de América del Sur, lo que las diferencia de la mayoría de sus congéneres estudiados en América del Norte.Colony size in ants is associated with important ecological characteristics such as foraging strategy. Though colony size has been studied with some detail for several North American species of Pogonomyrmex harvester ants, it remains unknown for South American species. We studied colony size, composition, and nest structure of three species of Pogonomyrmex harvester ants inhabiting the central Monte desert in Argentina: P. mendozanus Cuezzo & Claver, P. inermis Forel and P. rastratus Mayr. We excavated two nests of each

  15. The use of weaver ants (Oecophylla spp.) in tropical agriculture

    DEFF Research Database (Denmark)

    Offenberg, Hans Joachim

    2011-01-01

    Canopy dwelling weaver ants are widely distributed throughout the Old World Tropics where they build up high densities on their host trees. If managed properly the high number of ants will control a range of pest insects and benefit crop production. Simultaneously the ant larvae production, fuelled...... by the consumed pest insects, can be harvested and utilised for nutrition as they are tasty and high in proteins, vitamins and minerals. Thus, plantations may function as ant farms and in addition to plant production also hosts the production of edible animal protein. In this setup harmful pest insects are turned...... farming as a way forward to solve an increasing future demand for protein. Weaver ant farming may build on natural food collected by the ants or alternatively be boosted by feeding the ant colonies actively with protein and sugar. In both cases, when ant biocontrol is combined with ant farming...

  16. Algorithms

    Indian Academy of Sciences (India)

    algorithms such as synthetic (polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language ... ·1 x:=sln(theta) x : = sm(theta) 1. ~. Idl d.t Read A.B,C. ~ lei ~ Print x.y.z. L;;;J. Figure 2 Symbols used In flowchart language to rep- resent Assignment, Read.

  17. Algorithms

    Indian Academy of Sciences (India)

    In the previous articles, we have discussed various common data-structures such as arrays, lists, queues and trees and illustrated the widely used algorithm design paradigm referred to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted ...

  18. Recognition of social identity in ants

    DEFF Research Database (Denmark)

    Bos, Nick; d'Ettorre, Patrizia

    2012-01-01

    Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend...... of hydrocarbons present on the cuticle of every individual (the “label”). Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the “template”). A mismatch between label and template leads to rejection...... of the encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template...

  19. Discrimination Behavior in the Supercolonial Pharaoh Ant

    DEFF Research Database (Denmark)

    Pontieri, Luigi

    an increasing need to understand which factors promote the ecological dominance of these species, and particularly how the discrimination of both conspecifics and heterospecifics (including parasites) might influence structure and ecological success of invasive populations. In this PhD thesis I investigated...... the discrimination behavior of the invasive pharaoh ant (Monomorium pharaonis) as a model for other invasive and supercolonial ant species. The pharaoh ant is one of the few ant species that can be reared in the laboratory for many generations. Furthermore, the possibility to do controlled crosses of colonies...... provides the unique opportunity to establish colonies of different genetic composition. These traits make this species a suitable study subject to set up behavioral experiments that aim to investigate which factors, and to which extent, might influence the inter- and intraspecific discrimination abilities...

  20. Insecticide transfer efficiency and lethal load in Argentine ants

    International Nuclear Information System (INIS)

    Hooper-Bui, L.M.; Kwok, E.S.C.; Buchholz, B.A.; Rust, M.K.; Eastmond, D.A.; Vogel, J.S.

    2015-01-01

    Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14 C-sucrose, 14 C-hydramethylnon, and 14 C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). The distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. Bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.

  1. Insecticide transfer efficiency and lethal load in Argentine ants

    Science.gov (United States)

    Hooper-Bui, L. M.; Kwok, E. S. C.; Buchholz, B. A.; Rust, M. K.; Eastmond, D. A.; Vogel, J. S.

    2015-10-01

    Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of 14C-sucrose, 14C-hydramethylnon, and 14C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). The distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. Bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.

  2. Insecticide transfer efficiency and lethal load in Argentine ants

    Energy Technology Data Exchange (ETDEWEB)

    Hooper-Bui, L.M. [Department of Environmental Science, Louisiana State University, Baton Rouge, LA 70803 (United States); Department of Entomology, University of California, Riverside, CA 92521 (United States); Kwok, E.S.C. [Department of Cell Biology and Neuroscience, University of California, Riverside, CA 92521 (United States); Buchholz, B.A., E-mail: buchholz2@llnl.gov [Center for Accelerator Mass Spectrometry, Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States); Department of Environmental Toxicology, University of California, Davis, CA 95616 (United States); Rust, M.K. [Department of Entomology, University of California, Riverside, CA 92521 (United States); Eastmond, D.A. [Department of Cell Biology and Neuroscience, University of California, Riverside, CA 92521 (United States); Vogel, J.S. [Center for Accelerator Mass Spectrometry, Lawrence Livermore National Laboratory, Livermore, CA 94551 (United States)

    2015-10-15

    Trophallaxis between individual worker ants and the toxicant load in dead and live Argentine ants (Linepithema humile) in colonies exposed to fipronil and hydramethylnon experimental baits were examined using accelerator mass spectrometry (AMS). About 50% of the content of the crop containing trace levels of {sup 14}C-sucrose, {sup 14}C-hydramethylnon, and {sup 14}C-fipronil was shared between single donor and recipient ants. Dead workers and queens contained significantly more hydramethylnon (122.7 and 22.4 amol/μg ant, respectively) than did live workers and queens (96.3 and 10.4 amol/μg ant, respectively). Dead workers had significantly more fipronil (420.3 amol/μg ant) than did live workers (208.5 amol/μg ant), but dead and live queens had equal fipronil levels (59.5 and 54.3 amol/μg ant, respectively). The distribution of fipronil differed within the bodies of dead and live queens; the highest amounts of fipronil were recovered in the thorax of dead queens whereas live queens had the highest levels in the head. Resurgence of polygynous ant colonies treated with hydramethylnon baits may be explained by queen survival resulting from sublethal doses due to a slowing of trophallaxis throughout the colony. Bait strategies and dose levels for controlling insect pests need to be based on the specific toxicant properties and trophic strategies for targeting the entire colony.

  3. Ants (Formicidae): models for social complexity.

    Science.gov (United States)

    Smith, Chris R; Dolezal, Adam; Eliyahu, Dorit; Holbrook, C Tate; Gadau, Jürgen

    2009-07-01

    The family Formicidae (ants) is composed of more than 12,000 described species that vary greatly in size, morphology, behavior, life history, ecology, and social organization. Ants occur in most terrestrial habitats and are the dominant animals in many of them. They have been used as models to address fundamental questions in ecology, evolution, behavior, and development. The literature on ants is extensive, and the natural history of many species is known in detail. Phylogenetic relationships for the family, as well as within many subfamilies, are known, enabling comparative studies. Their ease of sampling and ecological variation makes them attractive for studying populations and questions relating to communities. Their sociality and variation in social organization have contributed greatly to an understanding of complex systems, division of labor, and chemical communication. Ants occur in colonies composed of tens to millions of individuals that vary greatly in morphology, physiology, and behavior; this variation has been used to address proximate and ultimate mechanisms generating phenotypic plasticity. Relatedness asymmetries within colonies have been fundamental to the formulation and empirical testing of kin and group selection theories. Genomic resources have been developed for some species, and a whole-genome sequence for several species is likely to follow in the near future; comparative genomics in ants should provide new insights into the evolution of complexity and sociogenomics. Future studies using ants should help establish a more comprehensive understanding of social life, from molecules to colonies.

  4. Discriminatory abilities of facultative slave-making ants and their slaves.

    Science.gov (United States)

    Włodarczyk, T

    2016-01-01

    Intra-colony odor variability can disturb ants' ability to discriminate against intruders. The evolutionary relevance of this phenomenon can be revealed by studies on colonies of slave-making ants in which the parasite, and not the host, is subject to selection pressures associated with living in a mixed colony. We examined how the European facultative slave-making species Formica sanguinea and its F. fusca slaves perform in discriminating ants from alien colonies. Results of behavioral assays showed that slave-maker ants respond with hostility to conspecific individuals from alien colonies but are relatively tolerant to alien slaves. Furthermore, the behavior of slaves indicated a limited ability to discriminate ants from alien parasitic colonies. The subdivision of colony fragments into mixed and species-separated groups demonstrated that contact with the parasite is necessary for F. fusca slaves to be re-accepted by former nestmates after a period of separation from the stock colony. The results presented in this paper are consistent with the following hypotheses: (1) F. sanguinea ants, as opposed to their slaves, are adapted to discriminate alien individuals in the conditions of odor variability found in a mixed-species colony, (2) the recognition of slaves by F. sanguinea ants involves a dedicated adaptive mechanism that prevents aggression toward them, (3) the odor of slaves is strongly influenced by the parasite with beneficial effect on the colony integrity.

  5. Aphid egg protection by ants: a novel aspect of the mutualism between the tree-feeding aphid Stomaphis hirukawai and its attendant ant Lasius productus

    Science.gov (United States)

    Matsuura, Kenji; Yashiro, Toshihisa

    2006-10-01

    Aphids often form mutualistic associations with ants, in which the aphids provide the ants with honeydew and the ants defend the aphids from predators. In this paper, we report aphid egg protection by ants as a novel aspect of the deeply interdependent relationship between a tree-feeding aphid and its attendant ant. The ant Lasius productus harbours oviparous females, males, and eggs of the hinoki cypress-feeding aphid Stomaphis hirukawai in its nests in winter. We investigated the behaviour of ants kept with aphid eggs in petri dishes to examine whether the ants recognise the aphid eggs and tend them or only provide a refuge for the aphids. Workers carried almost all of the aphid eggs into the nest within 24 h. The ants indiscriminately tended aphid eggs collected from their own colonies and those from other ant colonies. The ants cleaned the eggs and piled them up in the nest, and egg tending by ants dramatically increased aphid egg survival rates. Starving the ants showed no significant effect on aphid egg survivorship. Without ants, aphid eggs were rapidly killed by fungi. These results suggested that grooming by the ants protected the aphid eggs, at least, against pathogenic fungi. This hygienic service afforded by the ants seems indispensable for egg survival of these aphids in an environment rich in potentially pathogenic microorganisms.

  6. Kombinasi Firefly Algorithm-Tabu Search untuk Penyelesaian Traveling Salesman Problem

    Directory of Open Access Journals (Sweden)

    Riyan Naufal Hay's

    2017-07-01

    Full Text Available Traveling Salesman Problem (TSP adalah masalah optimasi kombinatorial klasik dan memiliki peran dalam perencanaan, penjadwalan, dan pencarian pada bidang rekayasa dan pengetahuan (Dong, 2012. TSP juga merupakan objek yang baik untuk menguji kinerja metode optimasi, beberapa metode seperti Cooperative Genetic Ant System (CGAS (Dong, 2012, Parallelized Genetic Ant Colony System (PGAS Particle Swarm Optimization and Ant Colony Optimization Algorithms (PSO–ACO (Elloumi, 2014, dan Ant Colony Hyper-Heuristics (ACO HH (Aziz, 2015 telah dikembangkan untuk memecahkan TSP. Sehingga, pada penelitian ini diimplementasikan kombinasi metode baru untuk meningkatkan akurasi penyelesaian TSP. Firefly Algorithm (FA merupakan salah satu algoritma yang dapat digunakan untuk memecahkan masalah optimasi kombinatorial (Layeb, 2014. FA merupakan algoritma yang berpotensi kuat dalam memecahkan kasus optimasi dibanding algoritma yang ada termasuk Particle Swarm Optimization (Yang, 2010. Namun, FA memiliki kekurangan dalam memecahkan masalah optimasi dengan skala besar (Baykasoğlu dan Ozsoy, 2014. Tabu Search (TS merupakan metode optimasi yang terbukti efektif untuk memecahkan masalah optimasi dengan skala besar (Pedro, 2013. Pada penelitian ini, TS akan diterapkan pada FA (FATS untuk memecahkan kasus TSP. Hasil FATS akan dibandingkan terhadap penelitian sebelumnya yaitu ACOHH. Perbandingan hasil menunjukan peningkatan akurasi sebesar 0.89% pada dataset Oliver30, 0.14% dataset Eil51, 3.81% dataset Eil76 dan 1.27% dataset KroA100.

  7. Performance Analysis of Hybrid Swarm Intelligence Rule Induction Algorithm

    OpenAIRE

    Nalini, C.; Kongu Engineering College; Balasubramnaie, P.; Kongu Engineering College

    2010-01-01

    Data mining is used to extract potential information from data base. Rule induction is used to extract information from data base and display it in IF-THEN rule format. First the classification algorithm builds a predictive model from the training data set and then measure the accuracy of the model by using test data set.This work proposes a hybrid rule induction algorithm using Cooperative Particle Swarm (PSO) with Tabu search (TS), and Ant Colony Optimization (ACO). Real world data base cons...

  8. Bioinspired computation in combinatorial optimization: algorithms and their computational complexity

    DEFF Research Database (Denmark)

    Neumann, Frank; Witt, Carsten

    2012-01-01

    Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these algorithms. This tutorials...... explains the most important results achieved in this area. The presenters show how runtime behavior can be analyzed in a rigorous way, in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling...

  9. Cryptococcus neoformans carried by Odontomachus bauri ants

    Directory of Open Access Journals (Sweden)

    Mariana Santos de Jesus

    2012-06-01

    Full Text Available Cryptococcus neoformans is the most common causative agent of cryptococcosis worldwide. Although this fungus has been isolated from a variety of organic substrates, several studies suggest that hollow trees constitute an important natural niche for C. neoformans. A previously surveyed hollow of a living pink shower tree (Cassia grandis positive for C. neoformans in the city of Rio de Janeiro, Brazil, was chosen for further investigation. Odontomachus bauri ants (trap-jaw ants found inside the hollow were collected for evaluation as possible carriers of Cryptococcus spp. Two out of 10 ants were found to carry phenoloxidase-positive colonies identified as C. neoformans molecular types VNI and VNII. The ants may have acted as a mechanical vector of C. neoformans and possibly contributed to the dispersal of the fungi from one substrate to another. To the best of our knowledge, this is the first report on the association of C. neoformans with ants of the genus Odontomachus.

  10. Evolution of Fungal enzymes in the attine ant symbiosis

    DEFF Research Database (Denmark)

    de Fine Licht, Henrik Hjarvard; Schiøtt, Morten; Boomsma, Jacobus Jan

    The attine ant symbiosis is characterized by ancient but varying degrees of diffuse co-evolution between the ants and their fungal cultivars. Domesticated fungi became dependent on vertical transmission by queens and the ant colonies came to rely on their symbiotic fungus for food and thus......, indirectly, on fungal enzymes to break down the plant material brought in by the ants as fungal substrate. The more than 210 extant fungus-growing ant species differ considerably in colony size, social complexity and substrate-use. Only the derived leaf-cutting ants are specialized on using fresh leaves...... as garden substrate, whereas the more basal genera use leaf litter, insect feces and insect carcasses. We hypothesized that enzyme activity of fungal symbionts has co-evolved with substrate use and we measured enzyme activities of fungus gardens in the field to test this, focusing particularly on plant...

  11. Entomopathogens Isolated from Invasive Ants and Tests of Their Pathogenicity

    Directory of Open Access Journals (Sweden)

    Maria Fernanda Miori de Zarzuela

    2012-01-01

    Full Text Available Some ant species cause severe ecological and health impact in urban areas. Many attempts have been tested to control such species, although they do not always succeed. Biological control is an alternative to chemical control and has gained great prominence in research, and fungi and nematodes are among the successful organisms controlling insects. This study aimed to clarify some questions regarding the biological control of ants. Invasive ant species in Brazil had their nests evaluated for the presence of entomopathogens. Isolated entomopathogens were later applied in colonies of Monomorium floricola under laboratory conditions to evaluate their effectiveness and the behavior of the ant colonies after treatment. The entomopathogenic nematodes Heterorhabditis sp. and Steinernema sp. and the fungi Beauveria bassiana, Metarhizium anisopliae, and Paecilomyces sp. were isolated from the invasive ant nests. M. floricola colonies treated with Steinernema sp. and Heterorhabditis sp. showed a higher mortality of workers than control. The fungus Beauveria bassiana caused higher mortality of M. floricola workers. However, no colony reduction or elimination was observed in any treatment. The defensive behaviors of ants, such as grooming behavior and colony budding, must be considered when using fungi and nematodes for biological control of ants.

  12. Algorithms

    Indian Academy of Sciences (India)

    In the program shown in Figure 1, we have repeated the algorithm. M times and we can make the following observations. Each block is essentially a different instance of "code"; that is, the objects differ by the value to which N is initialized before the execution of the. "code" block. Thus, we can now avoid the repetition of the ...

  13. Algorithms

    Indian Academy of Sciences (India)

    algorithms built into the computer corresponding to the logic- circuit rules that are used to .... For the purpose of carrying ou t ari thmetic or logical operations the memory is organized in terms .... In fixed point representation, one essentially uses integer arithmetic operators assuming the binary point to be at some point other ...

  14. Why do house-hunting ants recruit in both directions?

    NARCIS (Netherlands)

    Planqué, R.; Dechaume-Moncharmont, F.-X.; Franks, N.R.; Kovacs, T.; Marshall, J.A.R.

    2007-01-01

    To perform tasks, organisms often use multiple procedures. Explaining the breadth of such behavioural repertoires is not always straightforward. During house hunting, colonies of Temnothorax albipennis ants use a range of behaviours to organise their emigrations. In particular, the ants use tandem

  15. Patterns of male parentage in the fungus-growing ants

    DEFF Research Database (Denmark)

    Villesen, Palle; Boomsma, JJ

    2003-01-01

    Ant queens from eight species, covering three genera of lower and two genera of higher attine ants, have exclusively or predominantly single mating. The ensuing full-sib colonies thus have a strong potential reproductive conflict between the queen and the workers over male production...

  16. The cavity-nest ant Temnothorax crassispinus prefers larger nests.

    Science.gov (United States)

    Mitrus, S

    Colonies of the ant Temnothorax crassispinus inhabit mostly cavities in wood and hollow acorns. Typically in the field, nest sites that can be used by the ant are a limited resource. In a field experiment, it was investigated whether the ants prefer a specific size of nest, when different ones are available. In July 2011, a total of 160 artificial nests were placed in a beech-pine forest. Four artificial nests (pieces of wood with volume cavities, ca 415, 605, 730, and 980 mm 3 , respectively) were located on each square meter of the experimental plot. One year later, shortly before the emergence of new sexuals, the nests were collected. In July 2012, colonies inhabited more frequently bigger nests. Among queenright colonies, the ones which inhabited bigger nests had more workers. However, there was no relationship between volume of nest and number of workers for queenless colonies. Queenright colonies from bigger nests produced more sexual individuals, but there was no correlation between number of workers and sex allocation ratio, or between volume of nest and sex allocation ratio. In a laboratory experiment where ant colonies were kept in 470 and 860 mm 3 nests, larger colonies allocated more energy to produce sexual individuals. The results of this study show the selectivity of T. crassispinus ants regarding the size of nest cavity, and that the nest volume has an impact on life history parameters.

  17. The Pied Piper: A Parasitic Beetle's Melodies Modulate Ant Behaviours.

    Directory of Open Access Journals (Sweden)

    Andrea Di Giulio

    Full Text Available Ants use various communication channels to regulate their social organisation. The main channel that drives almost all the ants' activities and behaviours is the chemical one, but it is long acknowledged that the acoustic channel also plays an important role. However, very little is known regarding exploitation of the acoustical channel by myrmecophile parasites to infiltrate the ant society. Among social parasites, the ant nest beetles (Paussus are obligate myrmecophiles able to move throughout the colony at will and prey on the ants, surprisingly never eliciting aggression from the colonies. It has been recently postulated that stridulatory organs in Paussus might be evolved as an acoustic mechanism to interact with ants. Here, we survey the role of acoustic signals employed in the Paussus beetle-Pheidole ant system. Ants parasitised by Paussus beetles produce caste-specific stridulations. We found that Paussus can "speak" three different "languages", each similar to sounds produced by different ant castes (workers, soldiers, queen. Playback experiments were used to test how host ants respond to the sounds emitted by Paussus. Our data suggest that, by mimicking the stridulations of the queen, Paussus is able to dupe the workers of its host and to be treated as royalty. This is the first report of acoustic mimicry in a beetle parasite of ants.

  18. The Pied Piper: A Parasitic Beetle's Melodies Modulate Ant Behaviours.

    Science.gov (United States)

    Di Giulio, Andrea; Maurizi, Emanuela; Barbero, Francesca; Sala, Marco; Fattorini, Simone; Balletto, Emilio; Bonelli, Simona

    2015-01-01

    Ants use various communication channels to regulate their social organisation. The main channel that drives almost all the ants' activities and behaviours is the chemical one, but it is long acknowledged that the acoustic channel also plays an important role. However, very little is known regarding exploitation of the acoustical channel by myrmecophile parasites to infiltrate the ant society. Among social parasites, the ant nest beetles (Paussus) are obligate myrmecophiles able to move throughout the colony at will and prey on the ants, surprisingly never eliciting aggression from the colonies. It has been recently postulated that stridulatory organs in Paussus might be evolved as an acoustic mechanism to interact with ants. Here, we survey the role of acoustic signals employed in the Paussus beetle-Pheidole ant system. Ants parasitised by Paussus beetles produce caste-specific stridulations. We found that Paussus can "speak" three different "languages", each similar to sounds produced by different ant castes (workers, soldiers, queen). Playback experiments were used to test how host ants respond to the sounds emitted by Paussus. Our data suggest that, by mimicking the stridulations of the queen, Paussus is able to dupe the workers of its host and to be treated as royalty. This is the first report of acoustic mimicry in a beetle parasite of ants.

  19. Optimization and design of an aircraft’s morphing wing-tip demonstrator for drag reduction at low speed, Part I – Aerodynamic optimization using genetic, bee colony and gradient descent algorithms

    Directory of Open Access Journals (Sweden)

    Andreea Koreanschi

    2017-02-01

    Full Text Available In this paper, an ‘in-house’ genetic algorithm is described and applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The algorithm’s performances were studied from the convergence point of view, in accordance with design conditions. The algorithm was compared to two other optimization methods, namely the artificial bee colony and a gradient method, for two optimization objectives, and the results of the optimizations with each of the three methods were plotted on response surfaces obtained with the Monte Carlo method, to show that they were situated in the global optimum region. The optimization results for 16 wind tunnel test cases and 2 objective functions were presented. The 16 cases used for the optimizations were included in the experimental test plan for the morphing wing-tip demonstrator, and the results obtained using the displacements given by the optimizations were evaluated.

  20. ANTS AS BIOLOGICAL INDICATORS FOR MONITORING CHANGES IN ARID ENVIRONMENTS: LESSONS FOR MONITORING PROTECTED AREAS

    Science.gov (United States)

    The responses of ant communities to structural change (removal of an invasive were studied in a replicated experiment in a Chihuahuan Desert grassland. The results from sampling of ant communities by pit-fall trapping were validated by mapping ant colonies on the experimental plo...

  1. The Antsy Social Network: Determinants of Nest Structure and Arrangement in Asian Weaver Ants

    OpenAIRE

    Devarajan, Kadambari

    2016-01-01

    Asian weaver ants (Oecophylla smaragdina) are arboreal ants that are known to form mutualistic complexes with their host trees. They are eusocial ants that build elaborate nests in the canopy in tropical areas. A colony comprises of multiple nests, usually on multiple trees, and the boundaries of the colony may be difficult to identify. However, they provide the ideal model for studying group living in invertebrates since there are a definite number of nests for a given substrate, the tree. H...

  2. Metaheuristic algorithms for building Covering Arrays: A review

    Directory of Open Access Journals (Sweden)

    Jimena Adriana Timaná-Peña

    2016-09-01

    Full Text Available Covering Arrays (CA are mathematical objects used in the functional testing of software components. They enable the testing of all interactions of a given size of input parameters in a procedure, function, or logical unit in general, using the minimum number of test cases. Building CA is a complex task (NP-complete problem that involves lengthy execution times and high computational loads. The most effective methods for building CAs are algebraic, Greedy, and metaheuristic-based. The latter have reported the best results to date. This paper presents a description of the major contributions made by a selection of different metaheuristics, including simulated annealing, tabu search, genetic algorithms, ant colony algorithms, particle swarm algorithms, and harmony search algorithms. It is worth noting that simulated annealing-based algorithms have evolved as the most competitive, and currently form the state of the art.

  3. 2nd International Conference on Harmony Search Algorithm

    CERN Document Server

    Geem, Zong

    2016-01-01

    The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community.  This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications.  The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques.   This book ...

  4. A Two-Stage Algorithm for the Closed-Loop Location-Inventory Problem Model Considering Returns in E-Commerce

    Directory of Open Access Journals (Sweden)

    Yanhui Li

    2014-01-01

    Full Text Available Facility location and inventory control are critical and highly related problems in the design of logistics system for e-commerce. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Focusing on the existing problem in e-commerce logistics system, we formulate a closed-loop location-inventory problem model considering returned merchandise to minimize the total cost which is produced in both forward and reverse logistics networks. To solve this nonlinear mixed programming model, an effective two-stage heuristic algorithm named LRCAC is designed by combining Lagrangian relaxation with ant colony algorithm (AC. Results of numerical examples show that LRCAC outperforms ant colony algorithm (AC on optimal solution and computing stability. The proposed model is able to help managers make the right decisions under e-commerce environment.

  5. On the performance of an artificial bee colony optimization algorithm applied to the accident diagnosis in a PWR nuclear power plant

    International Nuclear Information System (INIS)

    Oliveira, Iona Maghali S. de; Schirru, Roberto; Medeiros, Jose A.C.C.

    2009-01-01

    The swarm-based algorithm described in this paper is a new search algorithm capable of locating good solutions efficiently and within a reasonable running time. The work presents a population-based search algorithm that mimics the food foraging behavior of honey bee swarms and can be regarded as belonging to the category of intelligent optimization tools. In its basic version, the algorithm performs a kind of random search combined with neighborhood search and can be used for solving multi-dimensional numeric problems. Following a description of the algorithm, this paper presents a new event classification system based exclusively on the ability of the algorithm to find the best centroid positions that correctly identifies an accident in a PWR nuclear power plant, thus maximizing the number of correct classification of transients. The simulation results show that the performance of the proposed algorithm is comparable to other population-based algorithms when applied to the same problem, with the advantage of employing fewer control parameters. (author)

  6. Ant nebula

    Science.gov (United States)

    1999-01-01

    A new Hubble Space Telescope image of a celestial object called the Ant Nebula may shed new light on the future demise of our Sun. The image is available at http://www.jpl.nasa.gov/pictures/wfpc . The nebula, imaged on July 20, 1997, and June 30, 1998, by Hubble's Wide Field and Planetary Camera 2, was observed by Drs. Raghvendra Sahai and John Trauger of NASA's Jet Propulsion Laboratory, Pasadena, Calif.; Bruce Balick of the University of Washington in Seattle; and Vincent Icke of Leiden University in the Netherlands. JPL designed and built the camera. The Ant Nebula, whose technical name is Mz3, resembles the head and thorax of an ant when observed with ground-based telescopes. The new Hubble image, with 10 times the resolution revealing 100 times more detail, shows the 'ant's' body as a pair of fiery lobes protruding from a dying, Sun- like star. The Ant Nebula is located between 3,000 and 6,000 light years from Earth in the southern constellation Norma. The image challenges old ideas about what happens to dying stars. This observation, along with other pictures of various remnants of dying stars called planetary nebulae, shows that our Sun's fate will probably be much more interesting, complex and dramatic than astronomers previously believed. Although the ejection of gas from the dying star in the Ant Nebula is violent, it does not show the chaos one might expect from an ordinary explosion, but instead shows symmetrical patterns. One possibility is that the central star has a closely orbiting companion whose gravitational tidal forces shape the outflowing gas. A second possibility is that as the dying star spins, its strong magnetic fields are wound up into complex shapes like spaghetti in an eggbeater. Electrically charged winds, much like those in our Sun's solar wind but millions of times denser and moving at speeds up to 1,000 kilometers per second (more than 600 miles per second) from the star, follow the twisted field lines on their way out into space

  7. Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

    Science.gov (United States)

    Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing

    2016-10-01

    Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.

  8. Influence of task switching costs on colony homeostasis

    Science.gov (United States)

    Jeanson, Raphaël; Lachaud, Jean-Paul

    2015-06-01

    In social insects, division of labour allows colonies to optimise the allocation of workers across all available tasks to satisfy colony requirements. The maintenance of stable conditions within colonies (homeostasis) requires that some individuals move inside the nest to monitor colony needs and execute unattended tasks. We developed a simple theoretical model to explore how worker mobility inside the nest and task switching costs influence the maintenance of stable levels of task-associated stimuli. Our results indicate that worker mobility in large colonies generates important task switching costs and is detrimental to colony homeostasis. Our study suggests that the balance between benefits and costs associated with the mobility of workers patrolling inside the nest depends on colony size. We propose that several species of ants with diverse life-history traits should be appropriate to test the prediction that the proportion of mobile workers should vary during colony ontogeny.

  9. The natural history of the arboreal ant, Crematogaster ashmeadi

    Directory of Open Access Journals (Sweden)

    Walter R. Tschinkel

    2002-07-01

    Full Text Available The arboreal ant, Crematogaster ashmeadi Emery (Hymenoptera: Formicidae, is the most dominant arboreal ant in the pine forests of the coastal plain of northern Florida. The majority of pine trees harbor a colony of these ants. The colonies inhabit multiple chambers abandoned by bark-mining caterpillars, especially those of the family Cossidae, in the outer bark of living pines. They also inhabit ground level termite galleries in the bark, often locating the queen in galleries. The density of chambers and ants is highest in the base of the tree and drops sharply with height on the trunk. Because chambers are formed in the inner layer of bark, they gradually move outward as more bark layers are laid down, eventually sloughing off the tree's outer surface. Chambers have a mean lifetime of about 25 yr. The abundant chambers in pine bark are excavated by a small population of caterpillars and accumulate over decades. Ant colonies also inhabit abandoned galleries of woodboring beetles in dead branches in the crowns of pines. Because newly mated queens found colonies in abandoned woodboring beetle galleries in the first dead branches that form on pine saplings, C. ashmeadi is dependent on cavities made by other insects throughout its life cycle, and does little if any excavation of its own. Mature colonies nest preferentially in chambers greater than 10 cm2 in area, a relatively rare chamber size. In natural pine forests, this does not seem to limit the ant's populations.

  10. Host ant independent oviposition in the parasitic butterfly Maculinea alcon

    DEFF Research Database (Denmark)

    Fürst, Matthias A; Nash, David Richard

    2010-01-01

    Parasitic Maculinea alcon butterflies can only develop in nests of a subset of available Myrmica ant species, so female butterflies have been hypothesized to preferentially lay eggs on plants close to colonies of the correct host ants. Previous correlational investigations of host......-ant-dependent oviposition in this and other Maculinea species have, however, shown equivocal results, leading to a long-term controversy over support for this hypothesis. We therefore conducted a controlled field experiment to study the egg-laying behaviour of M. alcon. Matched potted Gentiana plants were set out close...... to host-ant nests and non-host-ant nests, and the number and position of eggs attached were assessed. Our results show no evidence for host-ant-based oviposition in M. alcon, but support an oviposition strategy based on plant characteristics. This suggests that careful management of host-ant distribution...

  11. Fire Ant Bites

    Science.gov (United States)

    ... Favorite Name: Category: Share: Yes No, Keep Private Fire Ant Bites Share | Fire ants are aggressive, venomous insects that have pinching ... across the United States, even into Puerto Rico. Fire ant stings usually occur on the feet or ...

  12. Indigenous weaver ants and fruit fly control in Tanzanian smallholder mango production

    DEFF Research Database (Denmark)

    Kirkegaard, Nina; Offenberg, Joachim; Msogoya, Theodosy

    2016-01-01

    Weaver ant colonies in mango trees are reported to deter oviposition by fruit flies into the developing fruits and, with controlled ant colonies, this can be sufficiently effective to become incorporated into commercial practice. A widely-offered explanation for this deterrent effect is that patr......Weaver ant colonies in mango trees are reported to deter oviposition by fruit flies into the developing fruits and, with controlled ant colonies, this can be sufficiently effective to become incorporated into commercial practice. A widely-offered explanation for this deterrent effect...... mango growers in Tanzania, where typical practice is to harvestmature, but not ripe, fruits for local sale. Initial interviews with growers provide an estimate of 10-25% crop losses due to fruit fly infestation and no strong perception of any significant impact of weaver ant colonisation on these losses...

  13. A Combination of Meta-heuristic and Heuristic Algorithms for the VRP, OVRP and VRP with Simultaneous Pickup and Delivery

    Directory of Open Access Journals (Sweden)

    Maryam Ashouri

    2017-07-01

    Full Text Available Vehicle routing problem (VRP is a Nondeterministic Polynomial Hard combinatorial optimization problem to serve the consumers from central depots and returned back to the originated depots with given vehicles. Furthermore, two of the most important extensions of the VRPs are the open vehicle routing problem (OVRP and VRP with simultaneous pickup and delivery (VRPSPD. In OVRP, the vehicles have not return to the depot after last visit and in VRPSPD, customers require simultaneous delivery and pick-up service. The aim of this paper is to present a combined effective ant colony optimization (CEACO which includes sweep and several local search algorithms which is different with common ant colony optimization (ACO. An extensive numerical experiment is performed on benchmark problem instances addressed in the literature. The computational result shows that suggested CEACO approach not only presented a very satisfying scalability, but also was competitive with other meta-heuristic algorithms in the literature for solving VRP, OVRP and VRPSPD problems. Keywords: Meta-heuristic algorithms, Vehicle Routing Problem, Open Vehicle Routing Problem, Simultaneously Pickup and Delivery, Ant Colony Optimization.

  14. Design and implementation of intelligent electronic warfare decision making algorithm

    Science.gov (United States)

    Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

    2017-05-01

    Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

  15. Linear antenna array optimization using flower pollination algorithm.

    Science.gov (United States)

    Saxena, Prerna; Kothari, Ashwin

    2016-01-01

    Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

  16. Nature-inspired optimization algorithms

    CERN Document Server

    Yang, Xin-She

    2014-01-01

    Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning

  17. The ejaculatory biology of leafcutter ants

    DEFF Research Database (Denmark)

    den Boer, Susanne; Stürup, Marlene; Boomsma, Jacobus Jan

    2015-01-01

    The eusocial ants are unique in that females (queens) acquire and store sperm on a single mating flight early in adult life. This event largely determines the size (possibly millions of workers), longevity (possibly decades) and genetic variation of the colonies that queens found, but our...... understanding of the fundamental biology of ejaculate production, transfer and physiological function remains extremely limited. We studied the ejaculation process in the leafcutter ant Atta colombica and found that it starts with the appearance of a clear pre-ejaculatory fluid (PEF) at the tip...

  18. Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

    Science.gov (United States)

    Zirkohi, Majid Moradi

    2015-04-01

    The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

  19. Artificial ants deposit pheromone to search for regulatory DNA elements

    Directory of Open Access Journals (Sweden)

    Liu Yunlong

    2006-08-01

    Full Text Available Abstract Background Identification of transcription-factor binding motifs (DNA sequences can be formulated as a combinatorial problem, where an efficient algorithm is indispensable to predict the role of multiple binding motifs. An ant algorithm is a biology-inspired computational technique, through which a combinatorial problem is solved by mimicking the behavior of social insects such as ants. We developed a unique version of ant algorithms to select a set of binding motifs by considering a potential contribution of each of all random DNA sequences of 4- to 7-bp in length. Results Human chondrogenesis was used as a model system. The results revealed that the ant algorithm was able to identify biologically known binding motifs in chondrogenesis such as AP-1, NFκB, and sox9. Some of the predicted motifs were identical to those previously derived with the genetic algorithm. Unlike the genetic algorithm, however, the ant algorithm was able to evaluate a contribution of individual binding motifs as a spectrum of distributed information and predict core consensus motifs from a wider DNA pool. Conclusion The ant algorithm offers an efficient, reproducible procedure to predict a role of individual transcription-factor binding motifs using a unique definition of artificial ants.

  20. Designing communicating colonies of biomimetic microcapsules

    OpenAIRE

    Kolmakov, German V.; Yashin, Victor V.; Levitan, Steven P.; Balazs, Anna C.

    2010-01-01

    Using computational modeling, we design colonies of biomimetic microcapsules that exploit chemical mechanisms to communicate and alter their local environment. As a result, these synthetic objects can self-organize into various autonomously moving structures and exhibit ant-like tracking behavior. In the simulations, signaling microcapsules release agonist particles, whereas target microcapsules release antagonist particles and the permeabilities of both capsule types depend on the local part...

  1. Sperm length evolution in the fungus-growing ants

    DEFF Research Database (Denmark)

    Baer, B.; Dijkstra, M. B.; Mueller, U. G.

    2009-01-01

    Eusocial insects offer special opportunities for the comparative study of sperm traits because sperm competition is absent (in species with obligatory monandry) or constrained (in lineages where queens mate multiply but never remate later in life). We measured sperm length in 19 species of fungus......-growing ants, representing 9 of the 12 recognized genera, and mapped these onto the ant phylogeny. We show that average sperm length across species is highly variable and decreases with mature colony size in basal genera with singly mated queens, suggesting that sperm production or storage constraints affect...... the evolution of sperm length. Sperm length does not decrease further in multiply mating leaf-cutting ants, despite substantial further increases in colony size. In a combined analysis, sexual dimorphism explained 63.1% of the variance in sperm length between species. As colony size was not a significant...

  2. The Organization of Foraging in the Fire Ant, Solenopsis invicta

    Science.gov (United States)

    Tschinkel, Walter R.

    2011-01-01

    Although natural selection in ants acts most strongly at the colony, or superorganismal level, foraging patterns have rarely been studied at that level, focusing instead on the behavior of individual foragers or groups of foragers. The experiments and observations in this paper reveal in broad strokes how colonies of the fire ant, Solenopsis invicta Buren (Hymenoptera: Formicidae), allocate their available labor to foraging, how they disperse that force within their territory, and how this force changes with colony size, season and worker age. Territory area is positively related to colony size and the number of foragers, more so during the spring than fall. Changes of colony size and territory area are driven by seasonal variation of sexual and worker production, which in turn drive seasonal variation of worker age-distribution. During spring sexual production, colonies shrink because worker production falls below replacement. This loss is proportional to colony size, causing forager density in the spring to be negatively related to colony and territory size. In the fall, colonies emphasize worker production, bringing colony size back up. However, because smaller colonies curtailed spring worker production less than larger ones, their fall forager populations are proportionally greater, causing them to gain territory at the expense of large colonies. Much variation of territory area remains unexplained and can probably be attributed to pressure from neighboring colonies. Boundaries between territories are characterized by “no ants' zones” mostly devoid of fire ants. The forager population can be divided into a younger group of recruitable workers that wait for scouts to activate them to help retrieve large food finds. About one-third of the recruits wait near openings in the foraging tunnels that underlie the entire territory, while two-thirds wait in the nest. Recruitment to food is initially very rapid and local from the foraging tunnels, while sustained

  3. Interactive/automated method to count bacterial colonies

    OpenAIRE

    Monteiro, Fernando C.; Ribeiro, J.E.; Martins, Ramiro

    2016-01-01

    The number of colonies in a culture is counted to calculate the concentration of bacteria in the original broth; however, manual counting can be tedious, time-consuming and imprecise. Automation of colony counting has been of increasing interest for many decades, and these methods have been shown to be more consistent than manual counting. Significant limitations of many algorithms used in automated systems are their inability to recognize overlapping colonies as distinct and to count colonie...

  4. Disease dynamics in a specialized parasite of ant societies.

    Directory of Open Access Journals (Sweden)

    Sandra B Andersen

    Full Text Available Coevolution between ant colonies and their rare specialized parasites are intriguing, because lethal infections of workers may correspond to tolerable chronic diseases of colonies, but the parasite adaptations that allow stable coexistence with ants are virtually unknown. We explore the trade-offs experienced by Ophiocordyceps parasites manipulating ants into dying in nearby graveyards. We used field data from Brazil and Thailand to parameterize and fit a model for the growth rate of graveyards. We show that parasite pressure is much lower than the abundance of ant cadavers suggests and that hyperparasites often castrate Ophiocordyceps. However, once fruiting bodies become sexually mature they appear robust. Such parasite life-history traits are consistent with iteroparity--a reproductive strategy rarely considered in fungi. We discuss how tropical habitats with high biodiversity of hyperparasites and high spore mortality has likely been crucial for the evolution and maintenance of iteroparity in parasites with low dispersal potential.

  5. An Improved Artificial Bee Colony-Based Approach for Zoning Protected Ecological Areas.

    Directory of Open Access Journals (Sweden)

    Jing Shao

    Full Text Available China is facing ecological and environmental challenges as its urban growth rate continues to rise, and zoning protected ecological areas is recognized as an effective response measure. Zoning inherently involves both site attributes and aggregation attributes, and the combination of mathematical models and heuristic algorithms have proven advantageous. In this article, an improved artificial bee colony (IABC-based approach is proposed for zoning protected ecological areas at a regional scale. Three main improvements were made: the first is the use of multiple strategies to generate the initial bee population of a specific quality and diversity, the second is an exploitation search procedure to generate neighbor solutions combining "replace" and "alter" operations, and the third is a "swap" strategy to enable a local search for the iterative optimal solution. The IABC algorithm was verified using simulated data. Then it was applied to define an optimum scheme of protected ecological areas of Sanya (in the Hainan province of China, and a reasonable solution was obtained. Finally, a comparison experiment with other methods (agent-based land allocation model, ant colony optimization, and density slicing was conducted and demonstrated that the IABC algorithm was more effective and efficient than the other methods. Through this study, we aimed to provide a scientifically sound, practical approach for zoning procedures.

  6. Ant fat extraction with a Soxhlet extractor.

    Science.gov (United States)

    Smith, Chris R; Tschinkel, Walter R

    2009-07-01

    Stored fat can be informative about the relative age of an ant, its nutritional status, and the nutritional status of the colony. Several methods are available for the quantification of stored fat. Before starting a project involving fat extraction, investigators should weigh the advantages and disadvantages of different methods in order to choose the one that is best suited to the question being addressed. This protocol, although not as accurate as some alternatives, facilitates the rapid quantification of many individuals.

  7. How load-carrying ants avoid falling over: mechanical stability during foraging in Atta vollenweideri grass-cutting ants.

    Directory of Open Access Journals (Sweden)

    Karin Moll

    Full Text Available Foraging workers of grass-cutting ants (Atta vollenweideri regularly carry grass fragments larger than their own body. Fragment length has been shown to influence the ants' running speed and thereby the colony's food intake rate. We investigated whether and how grass-cutting ants maintain stability when carrying fragments of two different lengths but identical mass.Ants carried all fragments in an upright, backwards-tilted position, but held long fragments more vertically than short ones. All carrying ants used an alternating tripod gait, where mechanical stability was increased by overlapping stance phases of consecutive steps. The overlap was greatest for ants carrying long fragments, resulting in more legs contacting the ground simultaneously. For all ants, the projection of the total centre of mass (ant and fragment was often outside the supporting tripod, i.e. the three feet that would be in stance for a non-overlapping tripod gait. Stability was only achieved through additional legs in ground contact. Tripod stability (quantified as the minimum distance of the centre of mass to the edge of the supporting tripod was significantly smaller for ants with long fragments. Here, tripod stability was lowest at the beginning of each step, when the center of mass was near the posterior margin of the supporting tripod. By contrast, tripod stability was lowest at the end of each step for ants carrying short fragments. Consistently, ants with long fragments mainly fell backwards, whereas ants carrying short fragments mainly fell forwards or to the side. Assuming that transporting ants adjust neither the fragment angle nor the gait, they would be less stable and more likely to fall over.In grass-cutting ants, the need to maintain static stability when carrying long grass fragments has led to multiple kinematic adjustments at the expense of a reduced material transport rate.

  8. How load-carrying ants avoid falling over: mechanical stability during foraging in Atta vollenweideri grass-cutting ants.

    Science.gov (United States)

    Moll, Karin; Roces, Flavio; Federle, Walter

    2013-01-01

    Foraging workers of grass-cutting ants (Atta vollenweideri) regularly carry grass fragments larger than their own body. Fragment length has been shown to influence the ants' running speed and thereby the colony's food intake rate. We investigated whether and how grass-cutting ants maintain stability when carrying fragments of two different lengths but identical mass. Ants carried all fragments in an upright, backwards-tilted position, but held long fragments more vertically than short ones. All carrying ants used an alternating tripod gait, where mechanical stability was increased by overlapping stance phases of consecutive steps. The overlap was greatest for ants carrying long fragments, resulting in more legs contacting the ground simultaneously. For all ants, the projection of the total centre of mass (ant and fragment) was often outside the supporting tripod, i.e. the three feet that would be in stance for a non-overlapping tripod gait. Stability was only achieved through additional legs in ground contact. Tripod stability (quantified as the minimum distance of the centre of mass to the edge of the supporting tripod) was significantly smaller for ants with long fragments. Here, tripod stability was lowest at the beginning of each step, when the center of mass was near the posterior margin of the supporting tripod. By contrast, tripod stability was lowest at the end of each step for ants carrying short fragments. Consistently, ants with long fragments mainly fell backwards, whereas ants carrying short fragments mainly fell forwards or to the side. Assuming that transporting ants adjust neither the fragment angle nor the gait, they would be less stable and more likely to fall over. In grass-cutting ants, the need to maintain static stability when carrying long grass fragments has led to multiple kinematic adjustments at the expense of a reduced material transport rate.

  9. Moribund Ants Do Not Call for Help.

    Directory of Open Access Journals (Sweden)

    Krzysztof Miler

    Full Text Available When an antlion captures a foraging ant, the victim's nestmates may display rescue behaviour. This study tested the hypothesis that the expression of rescue behaviour depends on the life expectancy of the captured ant. This hypothesis predicts that the expression of rescue behaviour will be less frequent when the captured ant has a lower life expectancy than when it has a higher life expectancy because such a response would be adaptive at the colony level. Indeed, significant differences were found in the frequency of rescue behaviours in response to antlion victims with differing life expectancies. In agreement with prediction, victims with lower life expectancies were rescued less frequently, and those rescues had a longer latency and shorter duration. There was also a qualitative difference in the behaviour of rescuers to victims from the low and high life expectancy groups. Several explanations for these findings are proposed.

  10. Moribund Ants Do Not Call for Help.

    Science.gov (United States)

    Miler, Krzysztof

    2016-01-01

    When an antlion captures a foraging ant, the victim's nestmates may display rescue behaviour. This study tested the hypothesis that the expression of rescue behaviour depends on the life expectancy of the captured ant. This hypothesis predicts that the expression of rescue behaviour will be less frequent when the captured ant has a lower life expectancy than when it has a higher life expectancy because such a response would be adaptive at the colony level. Indeed, significant differences were found in the frequency of rescue behaviours in response to antlion victims with differing life expectancies. In agreement with prediction, victims with lower life expectancies were rescued less frequently, and those rescues had a longer latency and shorter duration. There was also a qualitative difference in the behaviour of rescuers to victims from the low and high life expectancy groups. Several explanations for these findings are proposed.

  11. The evolution of invasiveness in garden ants

    DEFF Research Database (Denmark)

    Cremer, Sylvia; Ugelvig, Line Vej; Drijfhout, Falko P

    2008-01-01

    It is unclear why some species become successful invaders whilst others fail, and whether invasive success depends on pre-adaptations already present in the native range or on characters evolving de-novo after introduction. Ants are among the worst invasive pests, with Lasius neglectus and its...... rapid spread through Europe and Asia as the most recent example of a pest ant that may become a global problem. Here, we present the first integrated study on behavior, morphology, population genetics, chemical recognition and parasite load of L. neglectus and its non-invasive sister species L. turcicus....... We find that L. neglectus expresses the same supercolonial syndrome as other invasive ants, a social system that is characterized by mating without dispersal and large networks of cooperating nests rather than smaller mutually hostile colonies. We conclude that the invasive success of L. neglectus...

  12. Neuromodulation of Nestmate Recognition Decisions by Pavement Ants.

    Directory of Open Access Journals (Sweden)

    Andrew N Bubak

    Full Text Available Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context-isolation, nestmate interaction, or fighting non-nestmates-affects brain monoamine levels in pavement ants (Tetramorium caespitum. Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants.

  13. Neuromodulation of Nestmate Recognition Decisions by Pavement Ants.

    Science.gov (United States)

    Bubak, Andrew N; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

    2016-01-01

    Ant colonies are distributed systems that are regulated in a non-hierarchical manner. Without a central authority, individuals inform their decisions by comparing information in local cues to a set of inherent behavioral rules. Individual behavioral decisions collectively change colony behavior and lead to self-organization capable of solving complex problems such as the decision to engage in aggressive societal conflicts with neighbors. Despite the relevance to colony fitness, the mechanisms that drive individual decisions leading to cooperative behavior are not well understood. Here we show how sensory information, both tactile and chemical, and social context-isolation, nestmate interaction, or fighting non-nestmates-affects brain monoamine levels in pavement ants (Tetramorium caespitum). Our results provide evidence that changes in octopamine and serotonin in the brains of individuals are sufficient to alter the decision by pavement ants to be aggressive towards non-nestmate ants whereas increased brain levels of dopamine correlate to physical fighting. We propose a model in which the changes in brain states of many workers collectively lead to the self-organization of societal aggression between neighboring colonies of pavement ants.

  14. Spatiotemporal resource distribution and foraging strategies of ants (Hymenoptera: Formicidae)

    Science.gov (United States)

    Lanan, Michele

    2014-01-01

    The distribution of food resources in space and time is likely to be an important factor governing the type of foraging strategy used by ants. However, no previous systematic attempt has been made to determine whether spatiotemporal resource distribution is in fact correlated with foraging strategy across the ants. In this analysis, I present data compiled from the literature on the foraging strategy and food resource use of 402 species of ants from across the phylogenetic tree. By categorizing the distribution of resources reported in these studies in terms of size relative to colony size, spatial distribution relative to colony foraging range, frequency of occurrence in time relative to worker life span, and depletability (i.e., whether the colony can cause a change in resource frequency), I demonstrate that different foraging strategies are indeed associated with specific spatiotemporal resource attributes. The general patterns I describe here can therefore be used as a framework to inform predictions in future studies of ant foraging behavior. No differences were found between resources collected via short-term recruitment strategies (group recruitment, short-term trails, and volatile recruitment), whereas different resource distributions were associated with solitary foraging, trunk trails, long-term trail networks, group raiding, and raiding. In many cases, ant species use a combination of different foraging strategies to collect diverse resources. It is useful to consider these foraging strategies not as separate options but as modular parts of the total foraging effort of a colony. PMID:25525497

  15. Dispersal Polymorphisms in Invasive Fire Ants.

    Directory of Open Access Journals (Sweden)

    Jackson A Helms

    Full Text Available In the Found or Fly (FoF hypothesis ant queens experience reproduction-dispersal tradeoffs such that queens with heavier abdomens are better at founding colonies but are worse flyers. We tested predictions of FoF in two globally invasive fire ants, Solenopsis geminata (Fabricius, 1804 and S. invicta (Buren, 1972. Colonies of these species may produce two different monogyne queen types-claustral queens with heavy abdomens that found colonies independently, and parasitic queens with small abdomens that enter conspecific nests. Claustral and parasitic queens were similarly sized, but the abdomens of claustral queens weighed twice as much as those of their parasitic counterparts. Their heavier abdomens adversely impacted morphological predictors of flight ability, resulting in 32-38% lower flight muscle ratios, 55-63% higher wing loading, and 32-33% higher abdomen drag. In lab experiments maximum flight durations in claustral S. invicta queens decreased by about 18 minutes for every milligram of abdomen mass. Combining our results into a simple fitness tradeoff model, we calculated that an average parasitic S. invicta queen could produce only 1/3 as many worker offspring as a claustral queen, but could fly 4 times as long and have a 17- to 36-fold larger potential colonization area. Investigations of dispersal polymorphisms and their associated tradeoffs promises to shed light on range expansions in invasive species, the evolution of alternative reproductive strategies, and the selective forces driving the recurrent evolution of parasitism in ants.

  16. Long-term disease dynamics for a specialized parasite of ant societies: a field study.

    Science.gov (United States)

    Loreto, Raquel G; Elliot, Simon L; Freitas, Mayara L R; Pereira, Thairine M; Hughes, David P

    2014-01-01

    Many studies have investigated how social insects behave when a parasite is introduced into their colonies. These studies have been conducted in the laboratory, and we still have a limited understanding of the dynamics of ant-parasite interactions under natural conditions. Here we consider a specialized parasite of ant societies (Ophiocordyceps camponoti-rufipedis infecting Camponotus rufipes) within a rainforest. We first established that the parasite is unable to develop to transmission stage when introduced within the host nest. Secondly, we surveyed all colonies in the studied area and recorded 100% prevalence at the colony level (all colonies were infected). Finally, we conducted a long-term detailed census of parasite pressure, by mapping the position of infected dead ants and foraging trails (future hosts) in the immediate vicinity of the colonies over 20 months. We report new dead infected ants for all the months we conducted the census--at an average of 14.5 cadavers/month/colony. Based on the low infection rate, the absence of colony collapse or complete recovery of the colonies, we suggest that this parasite represents a chronic infection in the ant societies. We also proposed a "terminal host model of transmission" that links the age-related polyethism to the persistence of a parasitic infection.

  17. Revolutionizing Remote Exploration with ANTS

    Science.gov (United States)

    Clark, P. E.; Rilee, M. L.; Curtis, S.; Truszkowski, W.

    2002-05-01

    We are developing the Autonomous Nano-Technology Swarm (ANTS) architecture based on an insect colony analogue for the cost-effective, efficient, systematic survey of remote or inaccessible areas with multiple object targets, including planetary surface, marine, airborne, and space environments. The mission context is the exploration in the 2020s of the most compelling remaining targets in the solar system: main belt asteroids. Main belt asteroids harbor important clues to Solar System origins and evolution which are central to NASA's goals in Space Science. Asteroids are smaller than planets, but their number is far greater, and their combined surface area likely dwarfs the Earth's. An asteroid survey will dramatically increase our understanding of the local resources available for the Human Exploration and Development of Space. During the mission composition, shape, gravity, and orbit parameters could be returned to Earth for perhaps several thousand asteroids. A survey of this area will rival the great explorations that encircled this globe, opened up the New World, and laid the groundwork for the progress and challenges of the last centuries. The ANTS architecture for a main belt survey consists of a swarm of as many as a thousand or more highly specialized pico-spacecraft that form teams to survey as many as one hundred asteroids a month. Multi-level autonomy is critical for ANTS and the objective of the proposed study is to work through the implications and constraints this entails. ANTS couples biologically inspired autonomic control for basic functions to higher level artificial intelligence that together enable individual spacecraft to operate as specialized, cooperative, social agents. This revolutionary approach postulates highly advanced, but familiar, components integrated and operated in a way that uniquely transcends any evolutionary extrapolation of existing trends and enables thousand-spacecraft missions.

  18. Mutualistic fungi control crop diversity in fungus-growing ants

    DEFF Research Database (Denmark)

    Poulsen, Michael; Boomsma, Jacobus J

    2005-01-01

    Leaf-cutting ants rear clonal fungi for food and transmit the fungi from mother to daughter colonies so that symbiont mixing and conflict, which result from competition between genetically different clones, are avoided. Here we show that despite millions of years of predominantly vertical...... transmission, the domesticated fungi actively reject mycelial fragments from neighboring colonies, and that the strength of these reactions are in proportion to the overall genetic difference between these symbionts. Fungal incompatibility compounds remain intact during ant digestion, so that fecal droplets...

  19. Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Cuiying Song

    2015-01-01

    Full Text Available This paper presents an improved genetic algorithm (GA with gene recombination for bus crew-scheduling problem in bus company. Unlike existing methods that rely on designing a fixed potential shift set by software, our new method does not need such a potential shift set information. In our method, satisfied shifts are generated through gene recombination in genetic algorithm. We conduct extensive studies based on real-life instances from Beijing Bus Group. Compared with results generated by the current manual method, ant colony algorithm, and CPLEX, computational results show that our algorithms demonstrated very good computational performances. In our tests, the number of the maximum reducing shifts can be beyond 30, especially when trip number is very large. The high relative percentage deviation demonstrated the effectiveness of the algorithm proposed.

  20. The search rate of the African weaver ant in cashew

    DEFF Research Database (Denmark)

    Henriksen, Signe; Axelsen, Jørgen Aagaard; Lemming, Katrine Hansen

    2015-01-01

    Oecophylla longinoda is a species of eusocial colony living ants that prey upon other insects to feed their larva. Many of these insects are considered pests. An ecosystem model of the interactions between an O. longinoda colony and its potential prey is under construction by the team behind...... this article, and it is unknown which functional response equations are useful for eusocial insect colonies. We investigated the search rate of O. longinoda using artificial feeding experiments in a Tanzanian cashew (Anacardium occidentale L.) orchard to determine the search efficiency of the ants......, and to assess which functional response equation can be used for eusocial insects. Artificial feeding experiments consisted of providing each of ten colonies 50 pieces of sardine (175 mg dry weight in average) in cashew trees at time 0 and counting the remaining food items at four intervals of 45 minutes during...

  1. Worker senescence and the sociobiology of aging in ants

    Science.gov (United States)

    Giraldo, Ysabel Milton; Traniello, James F. A.

    2014-01-01

    Senescence, the decline in physiological and behavioral function with increasing age, has been the focus of significant theoretical and empirical research in a broad array of animal taxa. Preeminent among invertebrate social models of aging are ants, a diverse and ecologically dominant clade of eusocial insects characterized by reproductive and sterile phenotypes. In this review, we critically examine selection for worker lifespan in ants and discuss the relationship between functional senescence, longevity, task performance, and colony fitness. We did not find strong or consistent support for the hypothesis that demographic senescence in ants is programmed, or its corollary prediction that workers that do not experience extrinsic mortality die at an age approximating their lifespan in nature. We present seven hypotheses concerning how selection could favor extended worker lifespan through its positive relationship to colony size and predict that large colony size, under some conditions, should confer multiple and significant fitness advantages. Fitness benefits derived from long worker lifespan could be mediated by increased resource acquisition, efficient division of labor, accuracy of collective decision-making, enhanced allomaternal care and colony defense, lower infection risk, and decreased energetic costs of workforce maintenance. We suggest future avenues of research to examine the evolution of worker lifespan and its relationship to colony fitness, and conclude that an innovative fusion of sociobiology, senescence theory, and mechanistic studies of aging can improve our understanding of the adaptive nature of worker lifespan in ants. PMID:25530660

  2. Nonrelatives inherit colony resources in a primitive termite.

    Science.gov (United States)

    Johns, Philip M; Howard, Kenneth J; Breisch, Nancy L; Rivera, Anahi; Thorne, Barbara L

    2009-10-13

    The evolution of eusociality, especially how selection would favor sterility or subfertility of most individuals within a highly social colony, is an unresolved paradox. Eusociality evolved independently in diverse taxa, including insects (all ants and termites; some bees, wasps, thrips, and beetles), snapping shrimp, and naked mole rats. Termites have received comparatively less focus than the haplodiploid Hymenoptera (ants, bees, and wasps); however, they are the only diploid group with highly complex colonies and an extraordinary diversity of castes. In this study we staged encounters between unrelated colonies of primitive dampwood termites, Zootermopsis nevadensis, mimicking natural meetings that occur under bark. During encounters, kings and/or queens were killed and surviving members merged into one colony. After encounters, members of both unrelated colonies cooperated as a single social unit. We determined the colony of origin of replacement reproductives that emerged after death of kings and/or queens. Here, we document that replacement reproductives developed from workers in either or both original colonies, inherited the merged resources of the colony, and sometimes interbred. Because this species shares many characteristics with ancestral termites, these findings demonstrate how ecological factors could have promoted the evolution of eusociality by accelerating and enhancing direct fitness opportunities of helper offspring, rendering relatedness favoring kin selection less critical.

  3. Effects of substrate, ant and fungal species on plant fiber degradation in a fungus-gardening ant symbiosis.

    Science.gov (United States)

    DeMilto, Alexandria M; Rouquette, Monte; Mueller, Ulrich G; Kellner, Katrin; Seal, Jon N

    2017-04-01

    Fungus-gardening or attine ants have outsourced most of their digestive function to a symbiotic fungus. The ants feed their fungus - essentially an external digestive organ - a variety of substrates of botanical origin, including fresh and dried flowers, leaves and insect frass (processed leaves). Although plant tissues are rich in fibers (lignocelluloses, hemicelluloses, pectins and starches) and the symbiotic fungus possesses the genetic and enzymatic machinery to metabolize these compounds, the highly derived attines, the leaf-cutters (Atta and Acromyrmex), are known to produce fiber-rich waste. While leaf-cutting ants are important consumers of primary plant tissue, there have been fewer studies on physiological activity of fungi grown by closely related ant species in the genus Trachymyrmex, which generally grow related species of fungi, have smaller colonies and consume a wider variety of fungal substrates in addition to fresh leaves and flowers. In this study, we measured the cellulase activity of the fungus-gardening ants Atta texana, Trachymyrmex arizonensis and T. septentrionalis. We then quantified fiber consumption of the fungus-gardening ants Trachymyrmex septentrionalis and Trachymyrmex arizonensis by comparing the amounts and percentages present in their food and in fungus garden refuse during a controlled feeding experiment over the span of several months. Finally, we compared waste composition of T. arizonensis colonies growing different fungal strains, because this species is known to cultivate multiple strains of Leucoagaricus in its native range. The leaf-cutting ant A. texana was found to have lower cellulytic activity than T. arizonensis or T. septentrionalis. Total lignocellulose and hemicellulose amounts were significantly lower in refuse piles than in the substrates fed to the Trachymyrmex colonies, thus these fibers were consumed by the fungal symbionts of these ant species. Although lignocellulose utilization was similar in two distinct

  4. Leaf endophyte load influences fungal garden development in leaf-cutting ants

    Directory of Open Access Journals (Sweden)

    Van Bael Sunshine A

    2012-11-01

    Full Text Available Abstract Background Previous work has shown that leaf-cutting ants prefer to cut leaf material with relatively low fungal endophyte content. This preference suggests that fungal endophytes exact a cost on the ants or on the development of their colonies. We hypothesized that endophytes may play a role in their host plants’ defense against leaf-cutting ants. To measure the long-term cost to the ant colony of fungal endophytes in their forage material, we conducted a 20-week laboratory experiment to measure fungal garden development for colonies that foraged on leaves with low or high endophyte content. Results Colony mass and the fungal garden dry mass did not differ significantly between the low and high endophyte feeding treatments. There was, however, a marginally significant trend toward greater mass of fungal garden per ant worker in the low relative to the high endophyte treatment. This trend was driven by differences in the fungal garden mass per worker from the earliest samples, when leaf-cutting ants had been foraging on low or high endophyte leaf material for only 2 weeks. At two weeks of foraging, the mean fungal garden mass per worker was 77% greater for colonies foraging on leaves with low relative to high endophyte loads. Conclusions Our data suggest that the cost of endophyte presence in ant forage material may be greatest to fungal colony development in its earliest stages, when there are few workers available to forage and to clean leaf material. This coincides with a period of high mortality for incipient colonies in the field. We discuss how the endophyte-leaf-cutter ant interaction may parallel constitutive defenses in plants, whereby endophytes reduce the rate of colony development when its risk of mortality is greatest.

  5. Comparative studies of the secretome of fungus-growing ants

    DEFF Research Database (Denmark)

    Linde, Tore; Grell, Morten Nedergaard; Schiøtt, Morten

    2009-01-01

    Leafcutter ants of the species Acromyrmex echinatior live in symbiosis with the fungus Leucoagaricus gongylophorus. The ants harvest fragments of leaves and carry them to the nest where they place the material on the fungal colony. The fungus secretes a wide array of proteins to degrade the leaves...... into nutrients that the ants can feed on. The focus of this study is to discover, characterize and compare the secreted proteins. In order to do so cDNA libraries are constructed from mRNA extracted from the fungus material. The most efficient technology to screen cDNA libraries selectively for secreted...

  6. Evolution of Fungal enzymes in the attine ant symbiosis

    DEFF Research Database (Denmark)

    de Fine Licht, Henrik Hjarvard; Schiøtt, Morten; Boomsma, Jacobus Jan

    The attine ant symbiosis is characterized by ancient but varying degrees of diffuse co-evolution between the ants and their fungal cultivars. Domesticated fungi became dependent on vertical transmission by queens and the ant colonies came to rely on their symbiotic fungus for food and thus...... as garden substrate, whereas the more basal genera use leaf litter, insect feces and insect carcasses. We hypothesized that enzyme activity of fungal symbionts has co-evolved with substrate use and we measured enzyme activities of fungus gardens in the field to test this, focusing particularly on plant...... essential for the symbiosis in general, but have contributed specifically to the evolution of the symbiosis....

  7. The Evolutionary Ecology of Multi-Queen Breeding in Ants

    DEFF Research Database (Denmark)

    Huszár, Dóra Borbála

    Ants, like other social insects, have evolved cooperative societies based on kinship. Colonies headed by a single breeding queen (monogyny) was the ancestral state but today ca. half of the ant species live in multi-queen societies (polygyny), which can sometimes reach extreme sizes (supercolony...... that only ants, not the other obligatorily social insects were able to decrease social and sexual conflicts sufficiently to make polygyny reach obligate form in some species. This can be explained by general ant biology, such as perennial lifehistories, foraging on foot instead of wings and having one...... mating event in life instead of ongoing events between pairs. Second, by empirical studies on the native ant species Myrmica rubra we were able to demonstrate that the three social syndromes can co-exist within populations, but with possible overlap in certain traits. Genetic and morphology results...

  8. The use of artificial nests by weaver ants: a preliminary field observation

    DEFF Research Database (Denmark)

    Offenberg, Joachim

    2014-01-01

    Weaver ants (Oecophylla spp.) are managed in tropical plantations for their biocontrol of pests and to produce ant larvae as a food source. Main management objectives are to increase ant densities and colony longevity. As weaver ant nests are susceptible to harsh weather, rain storms may decimate...... populations or destroy colonies. The ants, however, show adaptive nesting behavior, which may mitigate storm impact. This study tested whether Oecophylla smaragdina was willing to use plastic bottles as safe artificial nesting sites, and whether adoption of artificial nests was seasonally related to harsh...... weather. Bottles were used for nesting throughout the stormy rainy season in a pomelo plantation with an open canopy, whereas in a mango plantation with a denser canopy the ants, after initial colonisation, left the bottles again at the end of the rainy season, especially in the calmer part...

  9. Nutrition modifies critical thermal maximum of a dominant canopy ant.

    Science.gov (United States)

    Bujan, Jelena; Kaspari, Michael

    2017-10-01

    While adaptive responses to climate gradients are increasingly documented, little is known about how individuals alter their upper thermal tolerances. Long-term increases in dietary carbohydrates can elevate upper thermal tolerances in insects. We explored how the nutritional state of a Neotropical canopy ant governs its CT max - the temperature at which individuals lose muscle control. We predicted that Azteca chartifex workers recently fed a carbohydrate-rich diet, such as honeydew and extrafloral nectar, would use that energy to increase their CT max . Moreover, if a carbohydrate-rich diet increases CT max , then we predicted that ants from colonies with high CT max s feed at a lower trophic level, and thus have a higher carbon:nitrogen ratio. We used A. chartifex colonies from a long-term fertilization experiment where phosphorus addition increased A. chartifex foraging activity with respect to controls. As foraging activity can be governed by resource availability, we first measured CT max of field collected colonies. In freshly collected field colonies, CT max was 2°C higher in control plots. This difference disappeared when ants were provided with only water for 10h. Ants were then provided with a 10% sucrose solution ad lib which increased CT max by 5°C. We thus support the hypothesis that enhanced carbohydrate nutrition enables higher thermal tolerance, but this does not appear to be linked to colony trophic status, higher carbon:nitrogen ratios, or higher total body phosphorus. This short-term thermal plasticity linked to carbohydrate nutrition demonstrates the importance of ant diet in shaping their physiological traits. It is especially relevant to ant species that maintain high abundance by feeding on plant exudates. In a rapidly warming world, carbohydrate availability and use may represent a new element for predicting population and community responses of herbivorous insects. Copyright © 2017. Published by Elsevier Ltd.

  10. The importance of ants in cave ecology, with new records and behavioral observations of ants in Arizona caves

    Directory of Open Access Journals (Sweden)

    Robert B. Pape

    2016-09-01

    Full Text Available The importance of ants as elements in cave ecology has been mostly unrecognized. A global list of ant species recorded from caves, compiled from a review of existing literature, is presented. This paper also reviews what is currently known about ants occurring in Arizona (USA caves. The diversity and distribution represented in these records suggests ants are relatively common cave visitors (trogloxenes. A general utilization of caves by ants within both temperate and tropical latitudes may be inferred from this combined evidence. Observations of ant behavior in Arizona caves demonstrate a low level and sporadic, but persistent, use of these habitats and their contained resources by individual ant colonies. Documentation of Neivamyrmex sp. preying on cave-inhabiting arthropods is reported here for the first time. Observations of hypogeic army ants in caves suggests they may not penetrate to great vertical depth in search of prey, but can be persistent occupants in relatively shallow, horizontal sections of caves where they may prey on endemic cave animals. First cave records for ten ant species are reported from Arizona caves. These include two species of Neivamyrmex (N. nigrescens Cresson and Neivamyrmex sp.; Formicidae: Dorylinae, four myrmicines (Pheidole portalensis Wilson, Pheidole cf. porcula Wheeler, Solenopsis aurea Wheeler and Stenamma sp. Westwood, one dolichoderine (Forelius keiferi Wheeler and three formicines (Lasius arizonicus Wheeler, L. sitiens Wilson, and Camponotus sp. Mayr.

  11. Recruitment strategies and colony size in social insects

    NARCIS (Netherlands)

    Planque, R.; van den Berg, G.J.B.; Franks, N.R.

    2010-01-01

    Ants use a great variety of recruitment methods to forage for food or find new nests, including tandem running, group recruitment and scent trails. It has been known for some time that there is a loose correlation across many taxa between species-specific mature colony size and recruitment method.

  12. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Lazzús, Juan A., E-mail: jlazzus@dfuls.cl; Rivera, Marco; López-Caraballo, Carlos H.

    2016-03-11

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  13. Parameter estimation of Lorenz chaotic system using a hybrid swarm intelligence algorithm

    International Nuclear Information System (INIS)

    Lazzús, Juan A.; Rivera, Marco; López-Caraballo, Carlos H.

    2016-01-01

    A novel hybrid swarm intelligence algorithm for chaotic system parameter estimation is present. For this purpose, the parameters estimation on Lorenz systems is formulated as a multidimensional problem, and a hybrid approach based on particle swarm optimization with ant colony optimization (PSO–ACO) is implemented to solve this problem. Firstly, the performance of the proposed PSO–ACO algorithm is tested on a set of three representative benchmark functions, and the impact of the parameter settings on PSO–ACO efficiency is studied. Secondly, the parameter estimation is converted into an optimization problem on a three-dimensional Lorenz system. Numerical simulations on Lorenz model and comparisons with results obtained by other algorithms showed that PSO–ACO is a very powerful tool for parameter estimation with high accuracy and low deviations. - Highlights: • PSO–ACO combined particle swarm optimization with ant colony optimization. • This study is the first research of PSO–ACO to estimate parameters of chaotic systems. • PSO–ACO algorithm can identify the parameters of the three-dimensional Lorenz system with low deviations. • PSO–ACO is a very powerful tool for the parameter estimation on other chaotic system.

  14. Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Kerim Guney

    2015-01-01

    Full Text Available An evolutionary method based on backtracking search optimization algorithm (BSA is proposed for linear antenna array pattern synthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and phase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical examples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and flexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm optimization (PSO, genetic algorithm (GA, modified touring ant colony algorithm (MTACO, quadratic programming method (QPM, bacterial foraging algorithm (BFA, bees algorithm (BA, clonal selection algorithm (CLONALG, plant growth simulation algorithm (PGSA, tabu search algorithm (TSA, memetic algorithm (MA, nondominated sorting GA-2 (NSGA-2, multiobjective differential evolution (MODE, decomposition with differential evolution (MOEA/D-DE, comprehensive learning PSO (CLPSO, harmony search algorithm (HSA, seeker optimization algorithm (SOA, and mean variance mapping optimization (MVMO. The simulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.

  15. Hybrid chaotic ant swarm optimization

    International Nuclear Information System (INIS)

    Li Yuying; Wen Qiaoyan; Li Lixiang; Peng Haipeng

    2009-01-01

    Chaotic ant swarm optimization (CASO) is a powerful chaos search algorithm that is used to find the global optimum solution in search space. However, the CASO algorithm has some disadvantages, such as lower solution precision and longer computational time, when solving complex optimization problems. To resolve these problems, an improved CASO, called hybrid chaotic swarm optimization (HCASO), is proposed in this paper. The new algorithm introduces preselection operator and discrete recombination operator into the CASO; meanwhile it replaces the best position found by own and its neighbors' ants with the best position found by preselection operator and discrete recombination operator in evolution equation. Through testing five benchmark functions with large dimensionality, the experimental results show the new method enhances the solution accuracy and stability greatly, as well as reduces the computational time and computer memory significantly when compared to the CASO. In addition, we observe the results can become better with swarm size increasing from the sensitivity study to swarm size. And we gain some relations between problem dimensions and swam size according to scalability study.

  16. Behavioural and chemical studies of discrimination processes in the leaf-cutting ant Acromyrmex laticeps nigrosetosus (Forel, 1908

    Directory of Open Access Journals (Sweden)

    D. J. Souza

    Full Text Available Leaf-cutting ants live in symbiosis with a basidiomycete fungus that is exploited as a source of nutrients for ant larvae. Tests of brood transport revealed that Acromyrmex laticeps nigrosetosus workers did not discriminate a concolonial brood from an alien brood. The same result was observed with tests of fungus transport. Adult workers showed no aggressive behaviour to workers from other alien colonies (non-nestmates. There was no qualitative variation in the chemical profiles of larvae, pupae and adult workers from the different colonies. However, quantitative differences were observed between the different colonies. Hypotheses about the lack of intraspecific aggression in this subspecies of ants are discussed.

  17. Honey Bees Inspired Optimization Method: The Bees Algorithm

    Directory of Open Access Journals (Sweden)

    Ernesto Mastrocinque

    2013-11-01

    Full Text Available Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

  18. INTRODUCTION The tailor or weaver ants of genus Oecophylla ...

    African Journals Online (AJOL)

    INTRODUCTION. The tailor or weaver ants of genus Oecophylla. (Hymenoptera: Formicidae) are eusocial insects. They are obligately arboreal and are known for their unique nest building behaviour where workers construct nests by weaving together leaves using larval silk. Colonies can be extremely large with a mature ...

  19. Energy Efficient Routing in Wireless Sensor Networks based on Ant ...

    African Journals Online (AJOL)

    Wireless Sensor Networks (WSN's) have become an important and challenging research area in recent years. Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony ...

  20. Testing the adjustable threshold model for intruder recognition on Myrmica ants in the context of a social parasite

    DEFF Research Database (Denmark)

    Fürst, Matthias Alois; Durey, Maëlle; Nash, David Richard

    2012-01-01

    gains access to the ants' nests by mimicking their cuticular hydrocarbon recognition cues, which allows the parasites to blend in with their host ants. Myrmica rubra may be particularly susceptible to exploitation in this fashion as it has large, polydomous colonies with many queens and a very viscous...... population structure. We studied the mutual aggressive behaviour of My. rubra colonies based on predictions for recognition effectiveness. Three hypotheses were tested: first, that aggression increases with distance (geographical, genetic and chemical); second, that the more queens present in a colony...... and therefore the less-related workers within a colony, the less aggressively they will behave; and that colonies facing parasitism will be more aggressive than colonies experiencing less parasite pressure. Our results confirm all these predictions, supporting flexible aggression behaviour in Myrmica ants...