Genetic algorithms for protein threading.
Yadgari, J; Amir, A; Unger, R
1998-01-01
Despite many years of efforts, a direct prediction of protein structure from sequence is still not possible. As a result, in the last few years researchers have started to address the "inverse folding problem": Identifying and aligning a sequence to the fold with which it is most compatible, a process known as "threading". In two meetings in which protein folding predictions were objectively evaluated, it became clear that threading as a concept promises a real breakthrough, but that much improvement is still needed in the technique itself. Threading is a NP-hard problem, and thus no general polynomial solution can be expected. Still a practical approach with demonstrated ability to find optimal solutions in many cases, and acceptable solutions in other cases, is needed. We applied the technique of Genetic Algorithms in order to significantly improve the ability of threading algorithms to find the optimal alignment of a sequence to a structure, i.e. the alignment with the minimum free energy. A major progress reported here is the design of a representation of the threading alignment as a string of fixed length. With this representation validation of alignments and genetic operators are effectively implemented. Appropriate data structure and parameters have been selected. It is shown that Genetic Algorithm threading is effective and is able to find the optimal alignment in a few test cases. Furthermore, the described algorithm is shown to perform well even without pre-definition of core elements. Existing threading methods are dependent on such constraints to make their calculations feasible. But the concept of core elements is inherently arbitrary and should be avoided if possible. While a rigorous proof is hard to submit yet an, we present indications that indeed Genetic Algorithm threading is capable of finding consistently good solutions of full alignments in search spaces of size up to 10(70).
Exact and Heuristic Algorithms for Runway Scheduling
Malik, Waqar A.; Jung, Yoon C.
2016-01-01
This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
Gene selection heuristic algorithm for nutrigenomics studies.
Valour, D; Hue, I; Grimard, B; Valour, B
2013-07-15
Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.
A HYBRID HEURISTIC ALGORITHM FOR THE CLUSTERED TRAVELING SALESMAN PROBLEM
Directory of Open Access Journals (Sweden)
Mário Mestria
2016-04-01
Full Text Available ABSTRACT This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP. Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators and diversification (constructive heuristic and perturbation routine. In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is -hard since it includes the well-known Traveling Salesman Problem (TSP as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.
Petri nets SM-cover-based on heuristic coloring algorithm
Tkacz, Jacek; Doligalski, Michał
2015-09-01
In the paper, coloring heuristic algorithm of interpreted Petri nets is presented. Coloring is used to determine the State Machines (SM) subnets. The present algorithm reduces the Petri net in order to reduce the computational complexity and finds one of its possible State Machines cover. The proposed algorithm uses elements of interpretation of Petri nets. The obtained result may not be the best, but it is sufficient for use in rapid prototyping of logic controllers. Found SM-cover will be also used in the development of algorithms for decomposition, and modular synthesis and implementation of parallel logic controllers. Correctness developed heuristic algorithm was verified using Gentzen formal reasoning system.
A Direct Heuristic Algorithm for Linear Programming
Indian Academy of Sciences (India)
Abstract. An (3) mathematically non-iterative heuristic procedure that needs no artificial variable is presented for solving linear programming problems. An optimality test is included. Numerical experiments depict the utility/scope of such a procedure.
Heuristic and algorithmic processing in English, mathematics, and science education.
Sharps, Matthew J; Hess, Adam B; Price-Sharps, Jana L; Teh, Jane
2008-01-01
Many college students experience difficulties in basic academic skills. Recent research suggests that much of this difficulty may lie in heuristic competency--the ability to use and successfully manage general cognitive strategies. In the present study, the authors evaluated this possibility. They compared participants' performance on a practice California Basic Educational Skills Test and on a series of questions in the natural sciences with heuristic and algorithmic performance on a series of mathematics and reading comprehension exercises. Heuristic competency in mathematics was associated with better scores in science and mathematics. Verbal and algorithmic skills were associated with better reading comprehension. These results indicate the importance of including heuristic training in educational contexts and highlight the importance of a relatively domain-specific approach to questions of cognition in higher education.
Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites
Directory of Open Access Journals (Sweden)
Maocai Wang
2014-01-01
Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.
Seismic active control by a heuristic-based algorithm
International Nuclear Information System (INIS)
Tang, Yu.
1996-01-01
A heuristic-based algorithm for seismic active control is generalized to permit consideration of the effects of control-structure interaction and actuator dynamics. Control force is computed at onetime step ahead before being applied to the structure. Therefore, the proposed control algorithm is free from the problem of time delay. A numerical example is presented to show the effectiveness of the proposed control algorithm. Also, two indices are introduced in the paper to assess the effectiveness and efficiency of control laws
A novel heuristic algorithm for capacitated vehicle routing problem
Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre
2017-09-01
The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.
A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique
Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.
2018-04-01
Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.
Nuclear fuel management optimization using adaptive evolutionary algorithms with heuristics
International Nuclear Information System (INIS)
Axmann, J.K.; Van de Velde, A.
1996-01-01
Adaptive Evolutionary Algorithms in combination with expert knowledge encoded in heuristics have proved to be a robust and powerful optimization method for the design of optimized PWR fuel loading pattern. Simple parallel algorithmic structures coupled with a low amount of communications between computer processor units in use makes it possible for workstation clusters to be employed efficiently. The extension of classic evolution strategies not only by new and alternative methods but also by the inclusion of heuristics with effects on the exchange probabilities of the fuel assemblies at specific core positions leads to the RELOPAT optimization code of the Technical University of Braunschweig. In combination with the new, neutron-physical 3D nodal core simulator PRISM developed by SIEMENS the PRIMO loading pattern optimization system has been designed. Highly promising results in the recalculation of known reload plans for German PWR's new lead to a commercially usable program. (author)
A NEW HEURISTIC ALGORITHM FOR MULTIPLE TRAVELING SALESMAN PROBLEM
Directory of Open Access Journals (Sweden)
F. NURIYEVA
2017-06-01
Full Text Available The Multiple Traveling Salesman Problem (mTSP is a combinatorial optimization problem in NP-hard class. The mTSP aims to acquire the minimum cost for traveling a given set of cities by assigning each of them to a different salesman in order to create m number of tours. This paper presents a new heuristic algorithm based on the shortest path algorithm to find a solution for the mTSP. The proposed method has been programmed in C language and its performance analysis has been carried out on the library instances. The computational results show the efficiency of this method.
Identifying multiple influential spreaders by a heuristic clustering algorithm
Energy Technology Data Exchange (ETDEWEB)
Bao, Zhong-Kui [School of Mathematical Science, Anhui University, Hefei 230601 (China); Liu, Jian-Guo [Data Science and Cloud Service Research Center, Shanghai University of Finance and Economics, Shanghai, 200133 (China); Zhang, Hai-Feng, E-mail: haifengzhang1978@gmail.com [School of Mathematical Science, Anhui University, Hefei 230601 (China); Department of Communication Engineering, North University of China, Taiyuan, Shan' xi 030051 (China)
2017-03-18
The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.
Identifying multiple influential spreaders by a heuristic clustering algorithm
International Nuclear Information System (INIS)
Bao, Zhong-Kui; Liu, Jian-Guo; Zhang, Hai-Feng
2017-01-01
The problem of influence maximization in social networks has attracted much attention. However, traditional centrality indices are suitable for the case where a single spreader is chosen as the spreading source. Many times, spreading process is initiated by simultaneously choosing multiple nodes as the spreading sources. In this situation, choosing the top ranked nodes as multiple spreaders is not an optimal strategy, since the chosen nodes are not sufficiently scattered in networks. Therefore, one ideal situation for multiple spreaders case is that the spreaders themselves are not only influential but also they are dispersively distributed in networks, but it is difficult to meet the two conditions together. In this paper, we propose a heuristic clustering (HC) algorithm based on the similarity index to classify nodes into different clusters, and finally the center nodes in clusters are chosen as the multiple spreaders. HC algorithm not only ensures that the multiple spreaders are dispersively distributed in networks but also avoids the selected nodes to be very “negligible”. Compared with the traditional methods, our experimental results on synthetic and real networks indicate that the performance of HC method on influence maximization is more significant. - Highlights: • A heuristic clustering algorithm is proposed to identify the multiple influential spreaders in complex networks. • The algorithm can not only guarantee the selected spreaders are sufficiently scattered but also avoid to be “insignificant”. • The performance of our algorithm is generally better than other methods, regardless of real networks or synthetic networks.
A Modularity Degree Based Heuristic Community Detection Algorithm
Directory of Open Access Journals (Sweden)
Dongming Chen
2014-01-01
Full Text Available A community in a complex network can be seen as a subgroup of nodes that are densely connected. Discovery of community structures is a basic problem of research and can be used in various areas, such as biology, computer science, and sociology. Existing community detection methods usually try to expand or collapse the nodes partitions in order to optimize a given quality function. These optimization function based methods share the same drawback of inefficiency. Here we propose a heuristic algorithm (MDBH algorithm based on network structure which employs modularity degree as a measure function. Experiments on both synthetic benchmarks and real-world networks show that our algorithm gives competitive accuracy with previous modularity optimization methods, even though it has less computational complexity. Furthermore, due to the use of modularity degree, our algorithm naturally improves the resolution limit in community detection.
A New Approach to Tuning Heuristic Parameters of Genetic Algorithms
Czech Academy of Sciences Publication Activity Database
Holeňa, Martin
2006-01-01
Roč. 3, č. 3 (2006), s. 562-569 ISSN 1790-0832. [AIKED'06. WSEAS International Conference on Artificial Intelligence , Knowledge Engineering and Data Bases. Madrid, 15.02.2006-17.02.2006] R&D Projects: GA ČR(CZ) GA201/05/0325; GA ČR(CZ) GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary optimization * genetic algorithms * heuristic parameters * parameter tuning * artificial neural networks * convergence speed * population diversity Subject RIV: IN - Informatics, Computer Science
A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters
Directory of Open Access Journals (Sweden)
Weiwei Lin
2016-01-01
Full Text Available Cloud computing provides on-demand computing and storage services with high performance and high scalability. However, the rising energy consumption of cloud data centers has become a prominent problem. In this paper, we first introduce an energy-aware framework for task scheduling in virtual clusters. The framework consists of a task resource requirements prediction module, an energy estimate module, and a scheduler with a task buffer. Secondly, based on this framework, we propose a virtual machine power efficiency-aware greedy scheduling algorithm (VPEGS. As a heuristic algorithm, VPEGS estimates task energy by considering factors including task resource demands, VM power efficiency, and server workload before scheduling tasks in a greedy manner. We simulated a heterogeneous VM cluster and conducted experiment to evaluate the effectiveness of VPEGS. Simulation results show that VPEGS effectively reduced total energy consumption by more than 20% without producing large scheduling overheads. With the similar heuristic ideology, it outperformed Min-Min and RASA with respect to energy saving by about 29% and 28%, respectively.
Fast prediction of RNA-RNA interaction using heuristic algorithm.
Montaseri, Soheila
2015-01-01
Interaction between two RNA molecules plays a crucial role in many medical and biological processes such as gene expression regulation. In this process, an RNA molecule prohibits the translation of another RNA molecule by establishing stable interactions with it. Some algorithms have been formed to predict the structure of the RNA-RNA interaction. High computational time is a common challenge in most of the presented algorithms. In this context, a heuristic method is introduced to accurately predict the interaction between two RNAs based on minimum free energy (MFE). This algorithm uses a few dot matrices for finding the secondary structure of each RNA and binding sites between two RNAs. Furthermore, a parallel version of this method is presented. We describe the algorithm's concurrency and parallelism for a multicore chip. The proposed algorithm has been performed on some datasets including CopA-CopT, R1inv-R2inv, Tar-Tar*, DIS-DIS, and IncRNA54-RepZ in Escherichia coli bacteria. The method has high validity and efficiency, and it is run in low computational time in comparison to other approaches.
Solving SAT problem by heuristic polarity decision-making algorithm
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents a heuristic polarity decision-making algorithm for solving Boolean satisfiability (SAT). The algorithm inherits many features of the current state-of-the-art SAT solvers, such as fast BCP, clause recording, restarts, etc. In addition, a preconditioning step that calculates the polarities of variables according to the cover distribution of Karnaugh map is introduced into DPLL procedure, which greatly reduces the number of conflicts in the search process. The proposed approach is implemented as a SAT solver named DiffSat. Experiments show that DiffSat can solve many "real-life" instances in a reasonable time while the best existing SAT solvers, such as Zchaff and MiniSat, cannot. In particular, DiffSat can solve every instance of Bart benchmark suite in less than 0.03 s while Zchaff and MiniSat fail under a 900 s time limit. Furthermore, DiffSat even outperforms the outstanding incomplete algorithm DLM in some instances.
Runway Operations Planning: A Two-Stage Heuristic Algorithm
Anagnostakis, Ioannis; Clarke, John-Paul
2003-01-01
The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, can also be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. This paper introduces a two stage heuristic algorithm for solving the Runway Operations Planning (ROP) problem. In the first stage, sequences of departure class slots and runway crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program with a Branch & Bound algorithm implementation. Preliminary results from this implementation of the two-stage algorithm on real-world traffic data are presented.
Cost optimization model and its heuristic genetic algorithms
International Nuclear Information System (INIS)
Liu Wei; Wang Yongqing; Guo Jilin
1999-01-01
Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model
Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.
Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem
2018-01-01
In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.
Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.
Directory of Open Access Journals (Sweden)
Azmat Ullah
Full Text Available In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA with Interior Point Algorithm (IPA is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.
SIMPLE HEURISTIC ALGORITHM FOR DYNAMIC VM REALLOCATION IN IAAS CLOUDS
Directory of Open Access Journals (Sweden)
Nikita A. Balashov
2018-03-01
Full Text Available The rapid development of cloud technologies and its high prevalence in both commercial and academic areas have stimulated active research in the domain of optimal cloud resource management. One of the most active research directions is dynamic virtual machine (VM placement optimization in clouds build on Infrastructure-as-a-Service model. This kind of research may pursue different goals with energy-aware optimization being the most common goal as it aims at a urgent problem of green cloud computing - reducing energy consumption by data centers. In this paper we present a new heuristic algorithm of dynamic reallocation of VMs based on an approach presented in one of our previous works. In the algorithm we apply a 2-rank strategy to classify VMs and servers corresponding to the highly and lowly active VMs and solve four tasks: VM classification, host classification, forming a VM migration map and VMs migration. Dividing all of the VMs and servers into two classes we attempt to implement the possibility of risk reduction in case of hardware overloads under overcommitment conditions and to reduce the influence of the occurring overloads on the performance of the cloud VMs. Presented algorithm was developed based on the workload profile of the JINR cloud (a scientific private cloud with the goal of maximizing its usage, but it can also be applied in both public and private commercial clouds to organize the simultaneous use of different SLA and QoS levels in the same cloud environment by giving each VM rank its own level of overcommitment.
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505
Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda
2017-01-01
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.
Directory of Open Access Journals (Sweden)
D. A. Viattchenin
2009-01-01
Full Text Available A method for constructing a subset of labeled objects which is used in a heuristic algorithm of possible clusterization with partial training is proposed in the paper. The method is based on data preprocessing by the heuristic algorithm of possible clusterization using a transitive closure of a fuzzy tolerance. Method efficiency is demonstrated by way of an illustrative example.
Françoise Benz
2004-01-01
ACADEMIC TRAINING LECTURE REGULAR PROGRAMME 1, 2, 3 and 4 June From 11:00 hrs to 12:00 hrs - Main Auditorium bldg. 500 Evolutionary Heuristic Optimization: Genetic Algorithms and Estimation of Distribution Algorithms V. Robles Forcada and M. Perez Hernandez / Univ. de Madrid, Spain In the real world, there exist a huge number of problems that require getting an optimum or near-to-optimum solution. Optimization can be used to solve a lot of different problems such as network design, sets and partitions, storage and retrieval or scheduling. On the other hand, in nature, there exist many processes that seek a stable state. These processes can be seen as natural optimization processes. Over the last 30 years several attempts have been made to develop optimization algorithms, which simulate these natural optimization processes. These attempts have resulted in methods such as Simulated Annealing, based on natural annealing processes or Evolutionary Computation, based on biological evolution processes. Geneti...
Françoise Benz
2004-01-01
ENSEIGNEMENT ACADEMIQUE ACADEMIC TRAINING Françoise Benz 73127 academic.training@cern.ch ACADEMIC TRAINING LECTURE REGULAR PROGRAMME 1, 2, 3 and 4 June From 11:00 hrs to 12:00 hrs - Main Auditorium bldg. 500 Evolutionary Heuristic Optimization: Genetic Algorithms and Estimation of Distribution Algorithms V. Robles Forcada and M. Perez Hernandez / Univ. de Madrid, Spain In the real world, there exist a huge number of problems that require getting an optimum or near-to-optimum solution. Optimization can be used to solve a lot of different problems such as network design, sets and partitions, storage and retrieval or scheduling. On the other hand, in nature, there exist many processes that seek a stable state. These processes can be seen as natural optimization processes. Over the last 30 years several attempts have been made to develop optimization algorithms, which simulate these natural optimization processes. These attempts have resulted in methods such as Simulated Annealing, based on nat...
A genetic algorithm selection perturbative hyper-heuristic for solving ...
African Journals Online (AJOL)
Table 1: A summary of the characteristics of the artificial school timetabling problems. ..... One of the disadvantages of hyper-heuristics is the higher runtimes as a result .... 455–464 in AI 2002: Advances in Artificial Intelligence, Springer Berlin ...
A comparative study of the A* heuristic search algorithm used to solve efficiently a puzzle game
Iordan, A. E.
2018-01-01
The puzzle game presented in this paper consists in polyhedra (prisms, pyramids or pyramidal frustums) which can be moved using the free available spaces. The problem requires to be found the minimum number of movements in order the game reaches to a goal configuration starting from an initial configuration. Because the problem is enough complex, the principal difficulty in solving it is given by dimension of search space, that leads to necessity of a heuristic search. The improving of the search method consists into determination of a strong estimation by the heuristic function which will guide the search process to the most promising side of the search tree. The comparative study is realized among Manhattan heuristic and the Hamming heuristic using A* search algorithm implemented in Java. This paper also presents the necessary stages in object oriented development of a software used to solve efficiently this puzzle game. The modelling of the software is achieved through specific UML diagrams representing the phases of analysis, design and implementation, the system thus being described in a clear and practical manner. With the purpose to confirm the theoretical results which demonstrates that Manhattan heuristic is more efficient was used space complexity criterion. The space complexity was measured by the number of generated nodes from the search tree, by the number of the expanded nodes and by the effective branching factor. From the experimental results obtained by using the Manhattan heuristic, improvements were observed regarding space complexity of A* algorithm versus Hamming heuristic.
A Computational Investigation of Heuristic Algorithms for 2-Edge-Connectivity Augmentation
DEFF Research Database (Denmark)
Bang-Jensen, Jørgen; Chiarandini, Marco; Morling, Peter
2010-01-01
an equivalent set covering formulation. The results indicate that exact solutions by means of a basic integer programming model can be obtained in reasonably short time even on networks with 800 vertices and around 287,000 edges. Alternatively, an advanced heuristic algorithm based on subgradient...... programming, simple construction heuristics and metaheuristics. As part of the design of heuristics, we consider different neighborhood structures for local search, among which is a very large scale neighborhood. In all cases, we exploit approaches through the graph formulation as well as through...
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
A heuristic algorithm for computing the Poincar\\'e series of the invariants of binary forms
Djoković, Dragomir Ž.
2006-01-01
We propose a heuristic algorithm for fast computation of the Poincar\\'{e} series $P_n(t)$ of the invariants of binary forms of degree $n$, viewed as rational functions. The algorithm is based on certain polynomial identities which remain to be proved rigorously. By using it, we have computed the $P_n(t)$ for $n\\le30$.
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.
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Nadeem Javaid
2017-03-01
Full Text Available In recent years, demand side management (DSM techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart grid. In essence, five heuristic algorithms (the genetic algorithm (GA, the binary particle swarm optimization (BPSO algorithm, the bacterial foraging optimization algorithm (BFOA, the wind-driven optimization (WDO algorithm and our proposed hybrid genetic wind-driven (GWD algorithm are evaluated. These algorithms are used for scheduling residential loads between peak hours (PHs and off-peak hours (OPHs in a real-time pricing (RTP environment while maximizing user comfort (UC and minimizing both electricity cost and the peak to average ratio (PAR. Moreover, these algorithms are tested in two scenarios: (i scheduling the load of a single home and (ii scheduling the load of multiple homes. Simulation results show that our proposed hybrid GWD algorithm performs better than the other heuristic algorithms in terms of the selected performance metrics.
Shiangjen, Kanokwatt; Chaijaruwanich, Jeerayut; Srisujjalertwaja, Wijak; Unachak, Prakarn; Somhom, Samerkae
2018-02-01
This article presents an efficient heuristic placement algorithm, namely, a bidirectional heuristic placement, for solving the two-dimensional rectangular knapsack packing problem. The heuristic demonstrates ways to maximize space utilization by fitting the appropriate rectangle from both sides of the wall of the current residual space layer by layer. The iterative local search along with a shift strategy is developed and applied to the heuristic to balance the exploitation and exploration tasks in the solution space without the tuning of any parameters. The experimental results on many scales of packing problems show that this approach can produce high-quality solutions for most of the benchmark datasets, especially for large-scale problems, within a reasonable duration of computational time.
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Suresh K. Damodaran
2018-02-01
Full Text Available Hydro-thermal-wind generation scheduling (HTWGS with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to generate an hour-by-hour optimum schedule of hydro-thermal-wind power plants to attain the least emission of pollutants from thermal plants and a reduced generation cost of thermal and wind plants for a 24-h period, satisfying the system constraints. The paper presents a detailed framework of the HTWGS problem and proposes a modified particle swarm optimization (MPSO algorithm for evolving a solution. The competency of selected heuristic algorithms, representing different heuristic groups, viz. the binary coded genetic algorithm (BCGA, particle swarm optimization (PSO, improved harmony search (IHS, and JAYA algorithm, for searching for an optimal solution to HTWGS considering economic and environmental factors was investigated in a trial system consisting of a multi-stream cascaded system with four reservoirs, three thermal plants, and two wind plants. Appropriate mathematical models were used for representing the water discharge, generation cost, and pollutant emission of respective power plants incorporated in the system. Statistical analysis was performed to check the consistency and reliability of the proposed algorithm. The simulation results indicated that the proposed MPSO algorithm provided a better solution to the problem of HTWGS, with a reduced generation cost and the least emission, when compared with the other heuristic algorithms considered.
A heuristic algorithm for a multi-product four-layer capacitated location-routing problem
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Mohsen Hamidi
2014-01-01
Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.
Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks
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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.
Estimation of electricity demand of Iran using two heuristic algorithms
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Amjadi, M.H.; Nezamabadi-pour, H.; Farsangi, M.M.
2010-01-01
This paper deals with estimation of electricity demand of Iran based on economic indicators using Particle Swarm Optimization (PSO) Algorithm. The estimation is based on Gross Domestic Product (GDP), population, number of customers and average price electricity by developing two different estimation models: a linear model and a non-linear model. The proposed models are obtained based upon available actual data of 21 years; since 1980-2000. Then the models obtained are used to estimate the electricity demand of the target years; for a period of time e.g. 2001-2006 and the results obtained are compared with the actual demand during this period. Furthermore, to validate the results obtained by PSO, genetic algorithm (GA) is applied to solve the problem. The results show that the PSO is a useful optimization tool for solving the problem using two developed models and can be used as an alternative solution to estimate the future electricity demand.
A Heuristic Algorithm for Solving Triangle Packing Problem
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Ruimin Wang
2013-01-01
Full Text Available The research on the triangle packing problem has important theoretic significance, which has broad application prospects in material processing, network resource optimization, and so forth. Generally speaking, the orientation of the triangle should be limited in advance, since the triangle packing problem is NP-hard and has continuous properties. For example, the polygon is not allowed to rotate; then, the approximate solution can be obtained by optimization method. This paper studies the triangle packing problem by a new kind of method. Such concepts as angle region, corner-occupying action, corner-occupying strategy, and edge-conjoining strategy are presented in this paper. In addition, an edge-conjoining and corner-occupying algorithm is designed, which is to obtain an approximate solution. It is demonstrated that the proposed algorithm is highly efficient, and by the time complexity analysis and the analogue experiment result is found.
Expert System and Heuristics Algorithm for Cloud Resource Scheduling
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Mamatha E
2017-03-01
Full Text Available Rule-based scheduling algorithms have been widely used on cloud computing systems and there is still plenty of room to improve their performance. This paper proposes to develop an expert system to allocate resources in cloud by using Rule based Algorithm, thereby measuring the performance of the system by letting the system adapt new rules based on the feedback. Here performance of the action helps to make better allocation of the resources to improve quality of services, scalability and flexibility. The performance measure is based on how the allocation of the resources is dynamically optimized and how the resources are utilized properly. It aims to maximize the utilization of the resources. The data and resource are given to the algorithm which allocates the data to resources and an output is obtained based on the action occurred. Once the action is completed, the performance of every action is measured that contains how the resources are allocated and how efficiently it worked. In addition to performance, resource allocation in cloud environment is also considered.
Heuristic algorithms for the minmax regret flow-shop problem with interval processing times.
Ćwik, Michał; Józefczyk, Jerzy
2018-01-01
An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.
Application of Fuzzy Sets for the Improvement of Routing Optimization Heuristic Algorithms
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Mattas Konstantinos
2016-12-01
Full Text Available The determination of the optimal circular path has become widely known for its difficulty in producing a solution and for the numerous applications in the scope of organization and management of passenger and freight transport. It is a mathematical combinatorial optimization problem for which several deterministic and heuristic models have been developed in recent years, applicable to route organization issues, passenger and freight transport, storage and distribution of goods, waste collection, supply and control of terminals, as well as human resource management. Scope of the present paper is the development, with the use of fuzzy sets, of a practical, comprehensible and speedy heuristic algorithm for the improvement of the ability of the classical deterministic algorithms to identify optimum, symmetrical or non-symmetrical, circular route. The proposed fuzzy heuristic algorithm is compared to the corresponding deterministic ones, with regard to the deviation of the proposed solution from the best known solution and the complexity of the calculations needed to obtain this solution. It is shown that the use of fuzzy sets reduced up to 35% the deviation of the solution identified by the classical deterministic algorithms from the best known solution.
A HYBRID HEURISTIC ALGORITHM FOR SOLVING THE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM (RCPSP
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Juan Carlos Rivera
Full Text Available The Resource Constrained Project Scheduling Problem (RCPSP is a problem of great interest for the scientific community because it belongs to the class of NP-Hard problems and no methods are known that can solve it accurately in polynomial processing times. For this reason heuristic methods are used to solve it in an efficient way though there is no guarantee that an optimal solution can be obtained. This research presents a hybrid heuristic search algorithm to solve the RCPSP efficiently, combining elements of the heuristic Greedy Randomized Adaptive Search Procedure (GRASP, Scatter Search and Justification. The efficiency obtained is measured taking into account the presence of the new elements added to the GRASP algorithm taken as base: Justification and Scatter Search. The algorithms are evaluated using three data bases of instances of the problem: 480 instances of 30 activities, 480 of 60, and 600 of 120 activities respectively, taken from the library PSPLIB available online. The solutions obtained by the developed algorithm for the instances of 30, 60 and 120 are compared with results obtained by other researchers at international level, where a prominent place is obtained, according to Chen (2011.
Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm
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Hui Li
2017-01-01
Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.
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Muhammad Farhan Ausaf
2015-12-01
Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.
A heuristic approach to possibilistic clustering algorithms and applications
Viattchenin, Dmitri A
2013-01-01
The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects. The proposed approach can be used for solving different classification problems. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. Moreover, a technique for constructing a subset of the most appropriate alternatives for a set of weak fuzzy preference relations, which are defined on a universe of alternatives, is described in detail, and a method for rapidly prototyping the Mamdani’s fuzzy inference systems is introduced. This book addresses engineers, scientist...
Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem
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Mohammed Al-Salem
2016-01-01
Full Text Available The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD for a set of jobs when their weights equal 1 (unweighted problem. This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.
A hybrid heuristic algorithm for the open-pit-mining operational planning problem.
Souza, Marcone Jamilson Freitas; Coelho, Igor Machado; Ribas, Sabir; Santos, Haroldo Gambini; Merschmann, Luiz Henrique de Campos
2010-01-01
This paper deals with the Open-Pit-Mining Operational Planning problem with dynamic truck allocation. The objective is to optimize mineral extraction in the mines by minimizing the number of mining trucks used to meet production goals and quality requirements. According to the literature, this problem is NPhard, so a heuristic strategy is justified. We present a hybrid algorithm that combines characteristics of two metaheuristics: Greedy Randomized Adaptive Search Procedures and General Varia...
Design of application for graph's handling with heuristic algorithms of analysis
López, Carlos Andrés; Ardila Urueña, William
2008-01-01
El siguiente artículo muestra la manera de desarrollar una sencilla aplicación de entorno grafico sobre la cual se puede experimentar diversas técnicas, desde algoritmos de resolución de grafos hasta heurísticas empleadas en inteligencia artificial. The next section shows how to develop a simple graphical application environment on which to experiment with various techniques, from algorithms resolution graph until heuristics used in artificial intelligence.
Bakar, Sumarni Abu; Ibrahim, Milbah
2017-08-01
The shortest path problem is a popular problem in graph theory. It is about finding a path with minimum length between a specified pair of vertices. In any network the weight of each edge is usually represented in a form of crisp real number and subsequently the weight is used in the calculation of shortest path problem using deterministic algorithms. However, due to failure, uncertainty is always encountered in practice whereby the weight of edge of the network is uncertain and imprecise. In this paper, a modified algorithm which utilized heuristic shortest path method and fuzzy approach is proposed for solving a network with imprecise arc length. Here, interval number and triangular fuzzy number in representing arc length of the network are considered. The modified algorithm is then applied to a specific example of the Travelling Salesman Problem (TSP). Total shortest distance obtained from this algorithm is then compared with the total distance obtained from traditional nearest neighbour heuristic algorithm. The result shows that the modified algorithm can provide not only on the sequence of visited cities which shown to be similar with traditional approach but it also provides a good measurement of total shortest distance which is lesser as compared to the total shortest distance calculated using traditional approach. Hence, this research could contribute to the enrichment of methods used in solving TSP.
Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space
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Shaeen Kalathil
2015-11-01
Full Text Available This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB using canonic signed digit (CSD coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB.
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AYAS, S.
2018-02-01
Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
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DOGAN, A.
2018-02-01
Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
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T.A. Yakovleva
2011-05-01
Full Text Available This paper is dealing with the vehicle routing problem, where different types of vehicles are managing to deliver different types of products. Three step heuristic with genetic algorithm is proposed for solving the problem.
Jafari, Hamed; Salmasi, Nasser
2015-09-01
The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.
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Yahong Zheng
2014-05-01
Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.
A meta-heuristic method for solving scheduling problem: crow search algorithm
Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi
2018-04-01
Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.
Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie
2015-01-01
To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA.
Structure optimization by heuristic algorithm in a coarse-grained off-lattice model
International Nuclear Information System (INIS)
Jing-Fa, Liu
2009-01-01
A heuristic algorithm is presented for a three-dimensional off-lattice AB model consisting of hydrophobic (A) and hydrophilic (B) residues in Fibonacci sequences. By incorporating extra energy contributions into the original potential function, we convert the constrained optimization problem of AB model into an unconstrained optimization problem which can be solved by the gradient method. After the gradient minimization leads to the basins of the local energy minima, the heuristic off-trap strategy and subsequent neighborhood search mechanism are then proposed to get out of local minima and search for the lower-energy configurations. Furthermore, in order to improve the efficiency of the proposed algorithm, we apply the improved version called the new PERM with importance sampling (nPERMis) of the chain-growth algorithm, pruned-enriched-Rosenbluth method (PERM), to face-centered-cubic (FCC)-lattice to produce the initial configurations. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. In several cases, we found the ground state energies are lower than the best values reported in the present literature
Availability Allocation of Networked Systems Using Markov Model and Heuristics Algorithm
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Ruiying Li
2014-01-01
Full Text Available It is a common practice to allocate the system availability goal to reliability and maintainability goals of components in the early design phase. However, the networked system availability is difficult to be allocated due to its complex topology and multiple down states. To solve these problems, a practical availability allocation method is proposed. Network reliability algebraic methods are used to derive the availability expression of the networked topology on the system level, and Markov model is introduced to determine that on the component level. A heuristic algorithm is proposed to obtain the reliability and maintainability allocation values of components. The principles applied in the AGREE reliability allocation method, proposed by the Advisory Group on Reliability of Electronic Equipment, and failure rate-based maintainability allocation method persist in our allocation method. A series system is used to verify the new algorithm, and the result shows that the allocation based on the heuristic algorithm is quite accurate compared to the traditional one. Moreover, our case study of a signaling system number 7 shows that the proposed allocation method is quite efficient for networked systems.
Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms
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Rao, N.S.V. [Oak Ridge National Lab., TN (US); Kareti, S.; Shi, Weimin [Old Dominion Univ., Norfolk, VA (US). Dept. of Computer Science; Iyengar, S.S. [Louisiana State Univ., Baton Rouge, LA (US). Dept. of Computer Science
1993-07-01
A formal framework for navigating a robot in a geometric terrain by an unknown set of obstacles is considered. Here the terrain model is not a priori known, but the robot is equipped with a sensor system (vision or touch) employed for the purpose of navigation. The focus is restricted to the non-heuristic algorithms which can be theoretically shown to be correct within a given framework of models for the robot, terrain and sensor system. These formulations, although abstract and simplified compared to real-life scenarios, provide foundations for practical systems by highlighting the underlying critical issues. First, the authors consider the algorithms that are shown to navigate correctly without much consideration given to the performance parameters such as distance traversed, etc. Second, they consider non-heuristic algorithms that guarantee bounds on the distance traversed or the ratio of the distance traversed to the shortest path length (computed if the terrain model is known). Then they consider the navigation of robots with very limited computational capabilities such as finite automata, etc.
A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures
Kaveh, A.; Ilchi Ghazaan, M.
2018-02-01
In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.
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Orhan TÜRKBEY
2002-02-01
Full Text Available Memetic algorithms, which use local search techniques, are hybrid structured algorithms like genetic algorithms among evolutionary algorithms. In this study, for Quadratic Assignment Problem (QAP, a memetic structured algorithm using a local search heuristic like 2-opt is developed. Developed in the algorithm, a crossover operator that has not been used before for QAP is applied whereas, Eshelman procedure is used in order to increase thesolution variability. The developed memetic algorithm is applied on test problems taken from QAP-LIB, the results are compared with the present techniques in the literature.
Exact and Heuristic Algorithms for Routing AGV on Path with Precedence Constraints
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Liang Xu
2016-01-01
Full Text Available A new problem arises when an automated guided vehicle (AGV is dispatched to visit a set of customers, which are usually located along a fixed wire transmitting signal to navigate the AGV. An optimal visiting sequence is desired with the objective of minimizing the total travelling distance (or time. When precedence constraints are restricted on customers, the problem is referred to as traveling salesman problem on path with precedence constraints (TSPP-PC. Whether or not it is NP-complete has no answer in the literature. In this paper, we design dynamic programming for the TSPP-PC, which is the first polynomial-time exact algorithm when the number of precedence constraints is a constant. For the problem with number of precedence constraints, part of the input can be arbitrarily large, so we provide an efficient heuristic based on the exact algorithm.
Heuristic rules embedded genetic algorithm to solve VVER loading pattern optimization problem
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Fatih, Alim; Kostandi, Ivanov
2006-01-01
Full text: Loading Pattern (LP) optimization is one of the most important aspects of the operation of nuclear reactors. A genetic algorithm (GA) code GARCO (Genetic Algorithm Reactor Optimization Code) has been developed with embedded heuristic techniques to perform optimization calculations for in-core fuel management tasks. GARCO is a practical tool that includes a unique methodology applicable for all types of Pressurized Water Reactor (PWR) cores having different geometries with an unlimited number of FA types in the inventory. GARCO was developed by modifying the classical representation of the genotype. Both the genotype representation and the basic algorithm have been modified to incorporate the in-core fuel management heuristics rules so as to obtain the best results in a shorter time. GARCO has three modes. Mode 1 optimizes the locations of the fuel assemblies (FAs) in the nuclear reactor core, Mode 2 optimizes the placement of the burnable poisons (BPs) in a selected LP, and Mode 3 optimizes simultaneously both the LP and the BP placement in the core. This study describes the basic algorithm for Mode 1. The GARCO code is applied to the VVER-1000 reactor hexagonal geometry core in this study. The M oby-Dick i s used as reactor physics code to deplete FAs in the core. It was developed to analyze the VVER reactors by SKODA Inc. To use these rules for creating the initial population with GA operators, the worth definition application is developed. Each FA has a worth value for each location. This worth is between 0 and 1. If worth of any FA for a location is larger than 0.5, this FA in this location is a good choice. When creating the initial population of LPs, a subroutine provides a percent of individuals, which have genes with higher than the 0.5 worth. The percentage of the population to be created without using worth definition is defined in the GARCO input. And also age concept has been developed to accelerate the GA calculation process in reaching the
Foroughi Pour, Ali; Dalton, Lori A
2018-03-21
Many bioinformatics studies aim to identify markers, or features, that can be used to discriminate between distinct groups. In problems where strong individual markers are not available, or where interactions between gene products are of primary interest, it may be necessary to consider combinations of features as a marker family. To this end, recent work proposes a hierarchical Bayesian framework for feature selection that places a prior on the set of features we wish to select and on the label-conditioned feature distribution. While an analytical posterior under Gaussian models with block covariance structures is available, the optimal feature selection algorithm for this model remains intractable since it requires evaluating the posterior over the space of all possible covariance block structures and feature-block assignments. To address this computational barrier, in prior work we proposed a simple suboptimal algorithm, 2MNC-Robust, with robust performance across the space of block structures. Here, we present three new heuristic feature selection algorithms. The proposed algorithms outperform 2MNC-Robust and many other popular feature selection algorithms on synthetic data. In addition, enrichment analysis on real breast cancer, colon cancer, and Leukemia data indicates they also output many of the genes and pathways linked to the cancers under study. Bayesian feature selection is a promising framework for small-sample high-dimensional data, in particular biomarker discovery applications. When applied to cancer data these algorithms outputted many genes already shown to be involved in cancer as well as potentially new biomarkers. Furthermore, one of the proposed algorithms, SPM, outputs blocks of heavily correlated genes, particularly useful for studying gene interactions and gene networks.
An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems
Directory of Open Access Journals (Sweden)
R Subramanian
2013-12-01
Full Text Available The Economic Load Dispatch (ELD problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA, for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to limits on generator true power output and transmission losses. The MFA is a stochastic, Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of MFA to ELD for six generator test case system. MFA is applied to ELD problem and compared its solution quality and computation efficiency to Genetic algorithm (GA, Differential Evolution (DE, Particle swarm optimization (PSO, Artificial Bee Colony optimization (ABC, Biogeography-Based Optimization (BBO, Bacterial Foraging optimization (BFO, Firefly Algorithm (FA techniques. The simulation result shows that the proposed algorithm outperforms previous optimization methods.
Shrimp Feed Formulation via Evolutionary Algorithm with Power Heuristics for Handling Constraints
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Rosshairy Abd. Rahman
2017-01-01
Full Text Available Formulating feed for shrimps represents a challenge to farmers and industry partners. Most previous studies selected from only a small number of ingredients due to cost pressures, even though hundreds of potential ingredients could be used in the shrimp feed mix. Even with a limited number of ingredients, the best combination of the most appropriate ingredients is still difficult to obtain due to various constraint requirements, such as nutrition value and cost. This paper proposes a new operator which we call Power Heuristics, as part of an Evolutionary Algorithm (EA, which acts as a constraint handling technique for the shrimp feed or diet formulation. The operator is able to choose and discard certain ingredients by utilising a specialized search mechanism. The aim is to achieve the most appropriate combination of ingredients. Power Heuristics are embedded in the EA at the early stage of a semirandom initialization procedure. The resulting combination of ingredients, after fulfilling all the necessary constraints, shows that this operator is useful in discarding inappropriate ingredients when a crucial constraint is violated.
International Nuclear Information System (INIS)
Tahani, Mojtaba; Babayan, Narek; Astaraei, Fatemeh Razi; Moghadam, Ali
2015-01-01
Highlights: • The performance of four different Meta heuristic optimization algorithms was studied. • Power coefficient and produced torque on stationary blade were selected as objective functions. • Chord and twist distributions were selected as decision variables. • All optimization algorithms were combined with blade element momentum theory. • The best Pareto front was obtained by multi objective flower pollination algorithm for HATCTs. - Abstract: The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with blade element momentum theory (BEM). The second version of non-dominated sorting genetic algorithm (NSGA-II), multi objective particle swarm optimization algorithm (MOPSO), multi objective cuckoo search algorithm (MOCS) and multi objective flower pollination algorithm (MOFPA) are the selected algorithms. The power coefficient and the produced torque on stationary blade are selected as objective functions and chord and twist distributions along the blade span are selected as decision variables. These algorithms are combined with the blade element momentum (BEM) theory for the purpose of achieving the best Pareto front. The obtained Pareto fronts are compared with each other. Different sets of experiments are carried out by considering different numbers of iterations, population size and tip speed ratios. The Pareto fronts which are achieved by MOFPA and NSGA-II have better quality in comparison to MOCS and MOPSO, but on the other hand a detail comparison between the first fronts of MOFPA and NSGA-II indicated that MOFPA algorithm can obtain the best Pareto front and can maximize the power coefficient up to 4.3% and the
Meta-heuristic cuckoo search algorithm for the correction of faulty array antenna
International Nuclear Information System (INIS)
Khan, S.U.; Qureshi, I.M.
2015-01-01
In this article, we introduce a CSA (Cuckoo Search Algorithm) for compensation of faulty array antenna. It is assumed that the faulty elemental location is also known. When the sensor fails, it disturbs the power pattern, owing to which its SLL (Sidelobe Level) raises and nulls are shifted from their required positions. In this approach, the CSA optimizes the weights of the active elements for the reduction of SLL and null position in the desired direction. The meta-heuristic CSA is used for the control of SLL and steering of nulls at their required positions. The CSA is based on the necessitated kids bloodsucking behavior of cuckoo sort in arrangement with the Levy flight manners. The fitness function is used to reduce the error between the preferred and probable pattern along with null constraints. Imitational consequences for various scenarios are given to exhibit the validity and presentation of the proposed method. (author)
A Heuristic Scheduling Algorithm for Minimizing Makespan and Idle Time in a Nagare Cell
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M. Muthukumaran
2012-01-01
Full Text Available Adopting a focused factory is a powerful approach for today manufacturing enterprise. This paper introduces the basic manufacturing concept for a struggling manufacturer with limited conventional resources, providing an alternative solution to cell scheduling by implementing the technique of Nagare cell. Nagare cell is a Japanese concept with more objectives than cellular manufacturing system. It is a combination of manual and semiautomatic machine layout as cells, which gives maximum output flexibility for all kind of low-to-medium- and medium-to-high- volume productions. The solution adopted is to create a dedicated group of conventional machines, all but one of which are already available on the shop floor. This paper focuses on the development of heuristic scheduling algorithm in step-by-step method. The algorithm states that the summation of processing time of all products on each machine is calculated first and then the sum of processing time is sorted by the shortest processing time rule to get the assignment schedule. Based on the assignment schedule Nagare cell layout is arranged for processing the product. In addition, this algorithm provides steps to determine the product ready time, machine idle time, and product idle time. And also the Gantt chart, the experimental analysis, and the comparative results are illustrated with five (1×8 to 5×8 scheduling problems. Finally, the objective of minimizing makespan and idle time with greater customer satisfaction is studied through.
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Jeng-Fung Chen
2018-02-01
Full Text Available Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA, Cuckoo Optimization Algorithm (COA, and Cuckoo Search (CS are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA and multiple linear regression (MLR. In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.
Optimized LTE cell planning for multiple user density subareas using meta-heuristic algorithms
Ghazzai, Hakim
2014-09-01
Base station deployment in cellular networks is one of the most fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation 4G-LTE cellular networks using meta heuristic algorithms. In this approach, we aim to satisfy both coverage and cell capacity constraints simultaneously by formulating a practical optimization problem. We start by performing a typical coverage and capacity dimensioning to identify the initial required number of base stations. Afterwards, we implement a Particle Swarm Optimization algorithm or a recently-proposed Grey Wolf Optimizer to find the optimal base station locations that satisfy both problem constraints in the area of interest which can be divided into several subareas with different user densities. Subsequently, an iterative approach is executed to eliminate eventual redundant base stations. We have also performed Monte Carlo simulations to study the performance of the proposed scheme and computed the average number of users in outage. Results show that our proposed approach respects in all cases the desired network quality of services even for large-scale dimension problems.
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I Gusti Made Panji Indrawinatha
2016-12-01
Full Text Available Virus komputer merupakan perangkat lunak berbahaya yang dapat merusak data dan menggandakan diri pada sistem komputer. Untuk mendeteksi dan membersihkan virus dari sistem komputer, maka dibuatlah aplikasi antivirus. Dalam mendeteksi berbagai jenis virus sebuah aplikasi antivirus biasanya menggunakan beberapa metode. Pada penelitian ini akan membahas perancangan sebuah aplikasi antivirus menggunakan metode Secure Hash Algorithm 1 (SHA1 dan heuristic string sebagai metode pendeteksian virus. Dari pengujian yang dilakukan diperoleh hasil dimana saat tidak menggunakan heuristic, antivirus hanya mendeteksi 12 file dari 34 file sample virus atau memiliki tingkat akurasi pendeteksian sebesar 35%. sedangkan saat menggunakan heuristic, antivirus berhasil mendeteksi 31 file dari 34 file sample virus atau memiliki tingkat akurasi pendeteksian sebesar 91%.
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Igor Stojanović
2017-01-01
Full Text Available The continuous planar facility location problem with the connected region of feasible solutions bounded by arcs is a particular case of the constrained Weber problem. This problem is a continuous optimization problem which has a nonconvex feasible set of constraints. This paper suggests appropriate modifications of four metaheuristic algorithms which are defined with the aim of solving this type of nonconvex optimization problems. Also, a comparison of these algorithms to each other as well as to the heuristic algorithm is presented. The artificial bee colony algorithm, firefly algorithm, and their recently proposed improved versions for constrained optimization are appropriately modified and applied to the case study. The heuristic algorithm based on modified Weiszfeld procedure is also implemented for the purpose of comparison with the metaheuristic approaches. Obtained numerical results show that metaheuristic algorithms can be successfully applied to solve the instances of this problem of up to 500 constraints. Among these four algorithms, the improved version of artificial bee algorithm is the most efficient with respect to the quality of the solution, robustness, and the computational efficiency.
Heuristics of the algorithm: Big Data, user interpretation and institutional translation
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Göran Bolin
2015-10-01
Full Text Available Intelligence on mass media audiences was founded on representative statistical samples, analysed by statisticians at the market departments of media corporations. The techniques for aggregating user data in the age of pervasive and ubiquitous personal media (e.g. laptops, smartphones, credit cards/swipe cards and radio-frequency identification build on large aggregates of information (Big Data analysed by algorithms that transform data into commodities. While the former technologies were built on socio-economic variables such as age, gender, ethnicity, education, media preferences (i.e. categories recognisable to media users and industry representatives alike, Big Data technologies register consumer choice, geographical position, web movement, and behavioural information in technologically complex ways that for most lay people are too abstract to appreciate the full consequences of. The data mined for pattern recognition privileges relational rather than demographic qualities. We argue that the agency of interpretation at the bottom of market decisions within media companies nevertheless introduces a ‘heuristics of the algorithm’, where the data inevitably becomes translated into social categories. In the paper we argue that although the promise of algorithmically generated data is often implemented in automated systems where human agency gets increasingly distanced from the data collected (it is our technological gadgets that are being surveyed, rather than us as social beings, one can observe a felt need among media users and among industry actors to ‘translate back’ the algorithmically produced relational statistics into ‘traditional’ social parameters. The tenacious social structures within the advertising industries work against the techno-economically driven tendencies within the Big Data economy.
Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid
2017-10-01
Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.
Event based neutron activation spectroscopy and analysis algorithm using MLE and meta-heuristics
International Nuclear Information System (INIS)
Wallace, B.
2014-01-01
Techniques used in neutron activation analysis are often dependent on the experimental setup. In the context of developing a portable and high efficiency detection array, good energy resolution and half-life discrimination are difficult to obtain with traditional methods given the logistic and financial constraints. An approach different from that of spectrum addition and standard spectroscopy analysis was needed. The use of multiple detectors prompts the need for a flexible storage of acquisition data to enable sophisticated post processing of information. Analogously to what is done in heavy ion physics, gamma detection counts are stored as two-dimensional events. This enables post-selection of energies and time frames without the need to modify the experimental setup. This method of storage also permits the use of more complex analysis tools. Given the nature of the problem at hand, a light and efficient analysis code had to be devised. A thorough understanding of the physical and statistical processes involved was used to create a statistical model. Maximum likelihood estimation was combined with meta-heuristics to produce a sophisticated curve-fitting algorithm. Simulated and experimental data were fed into the analysis code prompting positive results in terms of half-life discrimination, peak identification and noise reduction. The code was also adapted to other fields of research such as heavy ion identification of the quasi-target (QT) and quasi-particle (QP). The approach used seems to be able to translate well into other fields of research. (author)
A heuristic algorithm to approximate dynamic program of a novel new product development process
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Hamed Fazlollahtabar
2016-01-01
Full Text Available We are concerned with a new product development (NPD network in digital environment in which the aim is to find integrated attributes for value added purposes. Different views exist for new product development. Here, the effective factors are categorized into customers, competitors and the company’s own past experience. Also, various attributes are considered for the development of a product. Thus, using digital data of attributes, the optimal set of attributes is chosen for user in the new product development. Regarding the multi stage decision making process of the customer, competitor and company’s own past experience, we develop a multi-dimensional dynamic program as a useful tool for multi stage decision making. To counteract the dynamism of the digital data in different time periods, two concepts of state and policy direction are introduced to determine the cost of moving through the stages of the proposed NPD digital network. Since the space requirements and value function computations become impractical for even moderate size, we approximate the optimal value function developing a heuristic algorithm.
Roozitalab, Ali; Asgharizadeh, Ezzatollah
2013-12-01
Warranty is now an integral part of each product. Since its length is directly related to the cost of production, it should be set in such a way that it would maximize revenue generation and customers' satisfaction. Furthermore, based on the behavior of customers, it is assumed that increasing the warranty period to earn the trust of more customers leads to more sales until the market is saturated. We should bear in mind that different groups of consumers have different consumption behaviors and that performance of the product has a direct impact on the failure rate over the life of the product. Therefore, the optimum duration for every group is different. In fact, we cannot present different warranty periods for various customer groups. In conclusion, using cuckoo meta-heuristic optimization algorithm, we try to find a common period for the entire population. Results with high convergence offer a term length that will maximize the aforementioned goals simultaneously. The study was tested using real data from Appliance Company. The results indicate a significant increase in sales when the optimization approach was applied; it provides a longer warranty through increased revenue from selling, not only reducing profit margins but also increasing it.
BiCluE - Exact and heuristic algorithms for weighted bi-cluster editing of biomedical data
DEFF Research Database (Denmark)
Sun, Peng; Guo, Jiong; Baumbach, Jan
2013-01-01
to solve the weighted bi-cluster editing problem. It implements (1) an exact algorithm based on fixed-parameter tractability and (2) a polynomial-time greedy heuristics based on solving the hardest part, edge deletions, first. We evaluated its performance on artificial graphs. Afterwards we exemplarily...... problem. BiCluE as well as the supplementary results are available online at http://biclue.mpi-inf.mpg.de webcite....
Multi-Threaded Algorithms for GPGPU in the ATLAS High Level Trigger
Conde Muíño, P.; ATLAS Collaboration
2017-10-01
General purpose Graphics Processor Units (GPGPU) are being evaluated for possible future inclusion in an upgraded ATLAS High Level Trigger farm. We have developed a demonstrator including GPGPU implementations of Inner Detector and Muon tracking and Calorimeter clustering within the ATLAS software framework. ATLAS is a general purpose particle physics experiment located on the LHC collider at CERN. The ATLAS Trigger system consists of two levels, with Level-1 implemented in hardware and the High Level Trigger implemented in software running on a farm of commodity CPU. The High Level Trigger reduces the trigger rate from the 100 kHz Level-1 acceptance rate to 1.5 kHz for recording, requiring an average per-event processing time of ∼ 250 ms for this task. The selection in the high level trigger is based on reconstructing tracks in the Inner Detector and Muon Spectrometer and clusters of energy deposited in the Calorimeter. Performing this reconstruction within the available farm resources presents a significant challenge that will increase significantly with future LHC upgrades. During the LHC data taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further to 7.5 times the design value in 2026 following LHC and ATLAS upgrades. Corresponding improvements in the speed of the reconstruction code will be needed to provide the required trigger selection power within affordable computing resources. Key factors determining the potential benefit of including GPGPU as part of the HLT processor farm are: the relative speed of the CPU and GPGPU algorithm implementations; the relative execution times of the GPGPU algorithms and serial code remaining on the CPU; the number of GPGPU required, and the relative financial cost of the selected GPGPU. We give a brief overview of the algorithms implemented and present new measurements that compare the performance of various configurations exploiting GPGPU cards.
Heuristic rules embedded genetic algorithm for in-core fuel management optimization
Alim, Fatih
The objective of this study was to develop a unique methodology and a practical tool for designing loading pattern (LP) and burnable poison (BP) pattern for a given Pressurized Water Reactor (PWR) core. Because of the large number of possible combinations for the fuel assembly (FA) loading in the core, the design of the core configuration is a complex optimization problem. It requires finding an optimal FA arrangement and BP placement in order to achieve maximum cycle length while satisfying the safety constraints. Genetic Algorithms (GA) have been already used to solve this problem for LP optimization for both PWR and Boiling Water Reactor (BWR). The GA, which is a stochastic method works with a group of solutions and uses random variables to make decisions. Based on the theories of evaluation, the GA involves natural selection and reproduction of the individuals in the population for the next generation. The GA works by creating an initial population, evaluating it, and then improving the population by using the evaluation operators. To solve this optimization problem, a LP optimization package, GARCO (Genetic Algorithm Reactor Code Optimization) code is developed in the framework of this thesis. This code is applicable for all types of PWR cores having different geometries and structures with an unlimited number of FA types in the inventory. To reach this goal, an innovative GA is developed by modifying the classical representation of the genotype. To obtain the best result in a shorter time, not only the representation is changed but also the algorithm is changed to use in-core fuel management heuristics rules. The improved GA code was tested to demonstrate and verify the advantages of the new enhancements. The developed methodology is explained in this thesis and preliminary results are shown for the VVER-1000 reactor hexagonal geometry core and the TMI-1 PWR. The improved GA code was tested to verify the advantages of new enhancements. The core physics code
Optimized LTE cell planning for multiple user density subareas using meta-heuristic algorithms
Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim
2014-01-01
Base station deployment in cellular networks is one of the most fundamental problems in network design. This paper proposes a novel method for the cell planning problem for the fourth generation 4G-LTE cellular networks using meta heuristic
FC-TLBO: fully constrained meta-heuristic algorithm for abundance ...
Indian Academy of Sciences (India)
Omprakash Tembhurne
hyperspectral unmixing; meta-heuristic approach; teaching-learning-based optimisation (TLBO). 1. ... area of research due to its real-time applications. Satellite .... describes the detailed methodology of proposed FC-TLBO. Section 4 contains ...
Directory of Open Access Journals (Sweden)
Jianhua Wang
2014-10-01
Full Text Available Purpose: The stable relationship of one-supplier-one-customer is replaced by a dynamic relationship of multi-supplier-multi-customer in current market gradually, and efficient scheduling techniques are important tools of the dynamic supply chain relationship establishing process. This paper studies the optimization of the integrated planning and scheduling problem of a two-stage supply chain with multiple manufacturers and multiple retailers to obtain a minimum supply chain operating cost, whose manufacturers have different production capacities, holding and producing cost rates, transportation costs to retailers.Design/methodology/approach: As a complex task allocation and scheduling problem, this paper sets up an INLP model for it and designs a Unit Cost Adjusting (UCA heuristic algorithm that adjust the suppliers’ supplying quantity according to their unit costs step by step to solve the model.Findings: Relying on the contrasting analysis between the UCA and the Lingo solvers for optimizing many numerical experiments, results show that the INLP model and the UCA algorithm can obtain its near optimal solution of the two-stage supply chain’s planning and scheduling problem within very short CPU time.Research limitations/implications: The proposed UCA heuristic can easily help managers to optimizing the two-stage supply chain scheduling problems which doesn’t include the delivery time and batch of orders. For two-stage supply chains are the most common form of actual commercial relationships, so to make some modification and study on the UCA heuristic should be able to optimize the integrated planning and scheduling problems of a supply chain with more reality constraints.Originality/value: This research proposes an innovative UCA heuristic for optimizing the integrated planning and scheduling problem of two-stage supply chains with the constraints of suppliers’ production capacity and the orders’ delivering time, and has a great
Directory of Open Access Journals (Sweden)
Mei-Shiang Chang
2013-01-01
Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.
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Yu Lin
2015-01-01
Full Text Available High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, frequency planning, and vehicle type choice in order to optimize the sum of the cost of transportation, inventory, and dispatch. To this end, we develop a mathematical model to describe the common frequency problem with vehicle type choice. Since the problem is NP hard, we develop a two-phase heuristic algorithm to solve the model. More specifically, an initial satisfactory solution is first generated through a greedy heuristic algorithm to maximize the ratio of the superior arc frequency to the inferior arc frequency. Following this, a tabu search (TS with limited search scope is used to improve the initial satisfactory solution. Numerical examples with different sizes establish the efficacy of our model and our proposed algorithm.
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Zhang Ziran
2018-01-01
Full Text Available In the study, context-creativity of Teresa M. Amabile was used as The foundation to apply it in the bags & luggage design course. Moreover, the sectional creative training education mode of prior heuristic task and postpositional algorithmic task was proposed. 26 junior students in product design were used as the trial objects. The Consensual Technique for Creativity (CAT was considered as the scoring standard of creative performance. In the end, the sectional theoretical framework of effective creative training in product design was finally proposed.
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Dawid Połap
2017-09-01
Full Text Available In the proposed article, we present a nature-inspired optimization algorithm, which we called Polar Bear Optimization Algorithm (PBO. The inspiration to develop the algorithm comes from the way polar bears hunt to survive in harsh arctic conditions. These carnivorous mammals are active all year round. Frosty climate, unfavorable to other animals, has made polar bears adapt to the specific mode of exploration and hunting in large areas, not only over ice but also water. The proposed novel mathematical model of the way polar bears move in the search for food and hunt can be a valuable method of optimization for various theoretical and practical problems. Optimization is very similar to nature, similarly to search for optimal solutions for mathematical models animals search for optimal conditions to develop in their natural environments. In this method. we have used a model of polar bear behaviors as a search engine for optimal solutions. Proposed simulated adaptation to harsh winter conditions is an advantage for local and global search, while birth and death mechanism controls the population. Proposed PBO was evaluated and compared to other meta-heuristic algorithms using sample test functions and some classical engineering problems. Experimental research results were compared to other algorithms and analyzed using various parameters. The analysis allowed us to identify the leading advantages which are rapid recognition of the area by the relevant population and efficient birth and death mechanism to improve global and local search within the solution space.
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Jeng-Fung Chen
2014-10-01
Full Text Available Predicting student academic performance with a high accuracy facilitates admission decisions and enhances educational services at educational institutions. This raises the need to propose a model that predicts student performance, based on the results of standardized exams, including university entrance exams, high school graduation exams, and other influential factors. In this study, an approach to the problem based on the artificial neural network (ANN with the two meta-heuristic algorithms inspired by cuckoo birds and their lifestyle, namely, Cuckoo Search (CS and Cuckoo Optimization Algorithm (COA is proposed. In particular, we used previous exam results and other factors, such as the location of the student’s high school and the student’s gender as input variables, and predicted the student academic performance. The standard CS and standard COA were separately utilized to train the feed-forward network for prediction. The algorithms optimized the weights between layers and biases of the neuron network. The simulation results were then discussed and analyzed to investigate the prediction ability of the neural network trained by these two algorithms. The findings demonstrated that both CS and COA have potential in training ANN and ANN-COA obtained slightly better results for predicting student academic performance in this case. It is expected that this work may be used to support student admission procedures and strengthen the service system in educational institutions.
Hebbar, Ullhas; Krishnan, Abilash; Kadoli, Ravikiran
2017-11-01
This work studied linear aspects of flow induced oscillations in cantilever pipes, with an emphasis on the numerical method of solution adopted for the system of governing equations. The complex frequencies of vibration of the different characteristic modes of the system were computed as a function of the flow velocity, wherein multi-variable minimization was performed using the popular Nelder-Mead heuristic algorithm. Results for a canonical fluid-to-pipe mass ratio (β) were validated with literature, and the evolution of frequencies was studied for different mass ratios. Additionally, the numerical scheme was implemented to compute critical conditions of stability for the cantilever system as a function of β. Finally, interesting aspects of the dynamics of the system were analyzed: the supposed `mode exchange' behavior, and an explanation for discontinuities observed in the critical conditions plotted as a function of β. In conclusion, the heuristic optimization based solution used in this study can be used to analyze various aspects of linear stability in pipes conveying fluid. Part of the submitted work was completed at the author's previous affiliation - National Institute of Technology Karnataka, India.
Zhou, Hui; Ji, Ning; Samuel, Oluwarotimi Williams; Cao, Yafei; Zhao, Zheyi; Chen, Shixiong; Li, Guanglin
2016-10-01
Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.
Proposal of Heuristic Algorithm for Scheduling of Print Process in Auto Parts Supplier
Matsumoto, Shimpei; Okuhara, Koji; Ueno, Nobuyuki; Ishii, Hiroaki
We are interested in the print process on the manufacturing processes of auto parts supplier as an actual problem. The purpose of this research is to apply our scheduling technique developed in university to the actual print process in mass customization environment. Rationalization of the print process is depending on the lot sizing. The manufacturing lead time of the print process is long, and in the present method, production is done depending on worker’s experience and intuition. The construction of an efficient production system is urgent problem. Therefore, in this paper, in order to shorten the entire manufacturing lead time and to reduce the stock, we reexamine the usual method of the lot sizing rule based on heuristic technique, and we propose the improvement method which can plan a more efficient schedule.
Heuristic space diversity management in a meta-hyper-heuristic framework
CSIR Research Space (South Africa)
Grobler, J
2014-07-01
Full Text Available This paper introduces the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm. Evaluation on a diverse set of floating...
Heuristic space diversity control for improved meta-hyper-heuristic performance
CSIR Research Space (South Africa)
Grobler, J
2015-04-01
Full Text Available This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits...
A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness
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Rui Zhang
2013-04-01
Full Text Available A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.
An Efficient Combined Meta-Heuristic Algorithm for Solving the Traveling Salesman Problem
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Majid Yousefikhoshbakht
2016-08-01
Full Text Available The traveling salesman problem (TSP is one of the most important NP-hard Problems and probably the most famous and extensively studied problem in the field of combinatorial optimization. In this problem, a salesman is required to visit each of n given nodes once and only once, starting from any node and returning to the original place of departure. This paper presents an efficient evolutionary optimization algorithm developed through combining imperialist competitive algorithm and lin-kernighan algorithm called (MICALK in order to solve the TSP. The MICALK is tested on 44 TSP instances involving from 24 to 1655 nodes from the literature so that 26 best known solutions of the benchmark problem are also found by our algorithm. Furthermore, the performance of MICALK is compared with several metaheuristic algorithms, including GA, BA, IBA, ICA, GSAP, ABO, PSO and BCO on 32 instances from TSPLIB. The results indicate that the MICALK performs well and is quite competitive with the above algorithms.
An Automatic Multilevel Image Thresholding Using Relative Entropy and Meta-Heuristic Algorithms
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Josue R. Cuevas
2013-06-01
Full Text Available Multilevel thresholding has been long considered as one of the most popular techniques for image segmentation. Multilevel thresholding outputs a gray scale image in which more details from the original picture can be kept, while binary thresholding can only analyze the image in two colors, usually black and white. However, two major existing problems with the multilevel thresholding technique are: it is a time consuming approach, i.e., finding appropriate threshold values could take an exceptionally long computation time; and defining a proper number of thresholds or levels that will keep most of the relevant details from the original image is a difficult task. In this study a new evaluation function based on the Kullback-Leibler information distance, also known as relative entropy, is proposed. The property of this new function can help determine the number of thresholds automatically. To offset the expensive computational effort by traditional exhaustive search methods, this study establishes a procedure that combines the relative entropy and meta-heuristics. From the experiments performed in this study, the proposed procedure not only provides good segmentation results when compared with a well known technique such as Otsu’s method, but also constitutes a very efficient approach.
H-PoP and H-PoPG: heuristic partitioning algorithms for single individual haplotyping of polyploids.
Xie, Minzhu; Wu, Qiong; Wang, Jianxin; Jiang, Tao
2016-12-15
Some economically important plants including wheat and cotton have more than two copies of each chromosome. With the decreasing cost and increasing read length of next-generation sequencing technologies, reconstructing the multiple haplotypes of a polyploid genome from its sequence reads becomes practical. However, the computational challenge in polyploid haplotyping is much greater than that in diploid haplotyping, and there are few related methods. This article models the polyploid haplotyping problem as an optimal poly-partition problem of the reads, called the Polyploid Balanced Optimal Partition model. For the reads sequenced from a k-ploid genome, the model tries to divide the reads into k groups such that the difference between the reads of the same group is minimized while the difference between the reads of different groups is maximized. When the genotype information is available, the model is extended to the Polyploid Balanced Optimal Partition with Genotype constraint problem. These models are all NP-hard. We propose two heuristic algorithms, H-PoP and H-PoPG, based on dynamic programming and a strategy of limiting the number of intermediate solutions at each iteration, to solve the two models, respectively. Extensive experimental results on simulated and real data show that our algorithms can solve the models effectively, and are much faster and more accurate than the recent state-of-the-art polyploid haplotyping algorithms. The experiments also show that our algorithms can deal with long reads and deep read coverage effectively and accurately. Furthermore, H-PoP might be applied to help determine the ploidy of an organism. https://github.com/MinzhuXie/H-PoPG CONTACT: xieminzhu@hotmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Heuristic algorithms for solving of the tool routing problem for CNC cutting machines
Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.
2015-11-01
The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.
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Markowski Marcin
2017-09-01
Full Text Available In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.
Energy Technology Data Exchange (ETDEWEB)
Perusquia del Cueto, R.; Montes T, J. L.; Ortiz S, J. J.; Castillo M, A., E-mail: raul.perusquia@inin.gob.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)
2011-11-15
At present the techniques of evolution al computation receive an increasing attention in the scientific and technological areas. This situation is due to its enormous potential in the optimization applied to problems of discussed computational complexity. In the nuclear area these techniques are used in diverse problems of combinatory optimization related with designing cores of power reactors. A distinctive characteristic of the evolution al and/or meta-heuristic algorithms is that appeal in each one from their applications to an adjustment function, fitness or of quality. This function allows to discriminate or to evaluate potentials solutions of the problem to solve. The definition of this situation is very important since it allows following the search of the algorithm toward different regions of the search space. In this work the impact that has the election of this function in the quality of the found solution is shown. The optimization technique by ant colonies or Acs (ant colony system) was used applied to the radial design of fuel cells for a boiling water power reactor. The notable results of the Acs allowed to propose the adjustment method of the importance and with this to obtain adjustment functions that guide the search of solutions of collective algorithms efficiently, basic capacity to develop the proposal of emulation of the natural selection and to investigate the possibility that on order of specify goals, to obtain the corresponding decision variables. A variety of re tro-exit (re tro-out) complementary process of feedback (re tro-in) that opens extended application perspectives of be feasible. (Author)
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Abdallah A. Hassan
2014-12-01
Full Text Available Optimizing autonomous vehicle movements through roadway intersections is a challenging problem. It has been demonstrated in the literature that traditional traffic control, such as traffic signal and stop sign control are not optimal especially for heavy traffic demand levels. Alternatively, centralized autonomous vehicle control strategies are costly and not scalable given that the ability of a central controller to track and schedule the movement of hundreds of vehicles in real-time is questionable. Consequently, in this paper a fully distributed algorithm is proposed where vehicles in the vicinity of an intersection continuously cooperate with each other to develop a schedule that allows them to safely proceed through the intersection while incurring minimum delay. Unlike other distributed approaches described in the literature, the wireless communication constraints are considered in the design of the control algorithm. Specifically, the proposed algorithm requires vehicles heading to an intersection to communicate only with neighboring vehicles, while the lead vehicles on each approach lane share information to develop a complete intersection utilization schedule. The scheduling rotates between vehicles to identify higher traffic volumes and favor vehicles coming from heavier lanes to minimize the overall intersection delay. The simulated experiments show significant reductions in the average delay using the proposed approach compared to other methods reported in the literature and reduction in the maximum delay experienced by a vehicle especially in cases of heavy traffic demand levels.
Wang, Wenrui; Wu, Yaohua; Wu, Yingying
2016-05-01
E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can't fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.
Huseyin Turan, Hasan; Kasap, Nihat; Savran, Huseyin
2014-03-01
Nowadays, every firm uses telecommunication networks in different amounts and ways in order to complete their daily operations. In this article, we investigate an optimisation problem that a firm faces when acquiring network capacity from a market in which there exist several network providers offering different pricing and quality of service (QoS) schemes. The QoS level guaranteed by network providers and the minimum quality level of service, which is needed for accomplishing the operations are denoted as fuzzy numbers in order to handle the non-deterministic nature of the telecommunication network environment. Interestingly, the mathematical formulation of the aforementioned problem leads to the special case of a well-known two-dimensional bin packing problem, which is famous for its computational complexity. We propose two different heuristic solution procedures that have the capability of solving the resulting nonlinear mixed integer programming model with fuzzy constraints. In conclusion, the efficiency of each algorithm is tested in several test instances to demonstrate the applicability of the methodology.
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Pholdee, Nantiwat; Bureerat, Su Jin [Khon Kaen University, Khon Kaen (Thailand); Baek, Hyun Moo [DTaQ, Changwon (Korea, Republic of); Im, Yong Taek [KAIST, Daejeon (Korea, Republic of)
2015-08-15
Process optimization of a Non-circular drawing (NCD) sequence of a pearlitic steel wire was performed to improve the mechanical properties of a drawn wire based on surrogate assisted meta-heuristic algorithms. The objective function was introduced to minimize inhomogeneity of effective strain distribution at the cross-section of the drawn wire, which could deteriorate delamination characteristics of the drawn wires. The design variables introduced were die geometry and reduction of area of the NCD sequence. Several surrogate models and their combinations with the weighted sum technique were utilized. In the process optimization of the NCD sequence, the surrogate models were used to predict effective strain distributions at the cross-section of the drawn wire. Optimization using Differential evolution (DE) algorithm was performed, while the objective function was calculated from the predicted effective strains. The accuracy of all surrogate models was investigated, while optimum results were compared with the previous study available in the literature. It was found that hybrid surrogate models can improve prediction accuracy compared to a single surrogate model. The best result was obtained from the combination of Kriging (KG) and Support vector regression (SVR) models, while the second best was obtained from the combination of four surrogate models: Polynomial response surface (PRS), Radial basic function (RBF), KG, and SVR. The optimum results found in this study showed better effective strain homogeneity at the cross-section of the drawn wire with the same total reduction of area of the previous work available in the literature for fewer number of passes. The multi-surrogate models with the weighted sum technique were found to be powerful in improving the delamination characteristics of the drawn wire and reducing the production cost.
A novel method for retinal optic disc detection using bat meta-heuristic algorithm.
Abdullah, Ahmad S; Özok, Yasa Ekşioğlu; Rahebi, Javad
2018-05-09
Normally, the optic disc detection of retinal images is useful during the treatment of glaucoma and diabetic retinopathy. In this paper, the novel preprocessing of a retinal image with a bat algorithm (BA) optimization is proposed to detect the optic disc of the retinal image. As the optic disk is a bright area and the vessels that emerge from it are dark, these facts lead to the selected segments being regions with a great diversity of intensity, which does not usually happen in pathological regions. First, in the preprocessing stage, the image is fully converted into a gray image using a gray scale conversion, and then morphological operations are implemented in order to remove dark elements such as blood vessels, from the images. In the next stage, a bat algorithm (BA) is used to find the optimum threshold value for the optic disc location. In order to improve the accuracy and to obtain the best result for the segmented optic disc, the ellipse fitting approach was used in the last stage to enhance and smooth the segmented optic disc boundary region. The ellipse fitting is carried out using the least square distance approach. The efficiency of the proposed method was tested on six publicly available datasets, MESSIDOR, DRIVE, DIARETDB1, DIARETDB0, STARE, and DRIONS-DB. The optic disc segmentation average overlaps and accuracy was in the range of 78.5-88.2% and 96.6-99.91% in these six databases. The optic disk of the retinal images was segmented in less than 2.1 s per image. The use of the proposed method improved the optic disc segmentation results for healthy and pathological retinal images in a low computation time. Graphical abstract ᅟ.
Helaers, Raphaël; Milinkovitch, Michel C
2010-07-15
The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high
Directory of Open Access Journals (Sweden)
Milinkovitch Michel C
2010-07-01
Full Text Available Abstract Background The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s but rather by practical issues such as ergonomics and/or the availability of specific functionalities. Results Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood, including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers. Conclusions The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these
M. Omidvari; M. R. Gharmaroudi
2015-01-01
Introduction: Occupational accidents are of the main issues in industries. It is necessary to identify the main root causes of accidents for their control. Several models have been proposed for determining the accidents root causes. FTA is one of the most widely used models which could graphically establish the root causes of accidents. The non-linear function is one of the main challenges in FTA compliance and in order to obtain the exact number, the meta-heuristic algorithms can be used. ...
Meta-Heuristics in Short Scale Construction: Ant Colony Optimization and Genetic Algorithm.
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.
Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey
Energy Technology Data Exchange (ETDEWEB)
Ceylan, Huseyin; Ceylan, Halim; Haldenbilen, Soner; Baskan, Ozgur [Department of Civil Engineering, Engineering Faculty, Pamukkale University, Muh. Fak. Denizli 20017 (Turkey)
2008-07-15
This study proposes a new method for estimating transport energy demand using a harmony search (HS) approach. HArmony Search Transport Energy Demand Estimation (HASTEDE) models are developed taking population, gross domestic product and vehicle kilometers as an input. The HASTEDE models are in forms of linear, exponential and quadratic mathematical expressions and they are applied to Turkish Transportation sector energy consumption. Optimum or near-optimum values of the HS parameters are obtained with sensitivity analysis (SA). Performance of all models is compared with the Ministry of Energy and Natural Resources (MENR) projections. Results showed that HS algorithm may be used for energy modeling, but SA is required to obtain best values of the HS parameters. The quadratic form of HASTEDE will overestimate transport sector energy consumption by about 26% and linear and exponential forms underestimate by about 21% when they are compared with the MENR projections. This may happen due to the modeling procedure and selected parameters for models, but determining the upper and lower values of transportation sector energy consumption will provide a framework and flexibility for setting up energy policies. (author)
Babaveisi, Vahid; Paydar, Mohammad Mahdi; Safaei, Abdul Sattar
2017-07-01
This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of maximizing the profit, minimizing the total risk and shortages of products. Since three objective functions are considered, a multi-objective solution methodology can be advantageous. Therefore, several approaches have been studied and an NSGA-II algorithm is first utilized, and then the results are validated using an MOSA and MOPSO algorithms. Priority-based encoding, which is used in all the algorithms, is the core of the solution computations. To compare the performance of the meta-heuristics, random numerical instances are evaluated by four criteria involving mean ideal distance, spread of non-dominance solution, the number of Pareto solutions, and CPU time. In order to enhance the performance of the algorithms, Taguchi method is used for parameter tuning. Finally, sensitivity analyses are performed and the computational results are presented based on the sensitivity analyses in parameter tuning.
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Ali Gerami Matin
2017-10-01
Full Text Available Optimized road maintenance planning seeks for solutions that can minimize the life-cycle cost of a road network and concurrently maximize pavement condition. Aiming at proposing an optimal set of road maintenance solutions, robust meta-heuristic algorithms are used in research. Two main optimization techniques are applied including single-objective and multi-objective optimization. Genetic algorithms (GA, particle swarm optimization (PSO, and combination of genetic algorithm and particle swarm optimization (GAPSO as single-objective techniques are used, while the non-domination sorting genetic algorithm II (NSGAII and multi-objective particle swarm optimization (MOPSO which are sufficient for solving computationally complex large-size optimization problems as multi-objective techniques are applied and compared. A real case study from the rural transportation network of Iran is employed to illustrate the sufficiency of the optimum algorithm. The formulation of the optimization model is carried out in such a way that a cost-effective maintenance strategy is reached by preserving the performance level of the road network at a desirable level. So, the objective functions are pavement performance maximization and maintenance cost minimization. It is concluded that multi-objective algorithms including non-domination sorting genetic algorithm II (NSGAII and multi-objective particle swarm optimization performed better than the single objective algorithms due to the capability to balance between both objectives. And between multi-objective algorithms the NSGAII provides the optimum solution for the road maintenance planning.
Real-time inextensible surgical thread simulation.
Xu, Lang; Liu, Qian
2018-03-27
This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects. The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations. Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method. Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.
Bergstra, J.A.; Middelburg, C.A.
2015-01-01
We add probabilistic features to basic thread algebra and its extensions with thread-service interaction and strategic interleaving. Here, threads represent the behaviours produced by instruction sequences under execution and services represent the behaviours exhibited by the components of execution
Ayvaz, M. Tamer
2007-11-01
This study proposes an inverse solution algorithm through which both the aquifer parameters and the zone structure of these parameters can be determined based on a given set of observations on piezometric heads. In the zone structure identification problem fuzzy c-means ( FCM) clustering method is used. The association of the zone structure with the transmissivity distribution is accomplished through an optimization model. The meta-heuristic harmony search ( HS) algorithm, which is conceptualized using the musical process of searching for a perfect state of harmony, is used as an optimization technique. The optimum parameter zone structure is identified based on three criteria which are the residual error, parameter uncertainty, and structure discrimination. A numerical example given in the literature is solved to demonstrate the performance of the proposed algorithm. Also, a sensitivity analysis is performed to test the performance of the HS algorithm for different sets of solution parameters. Results indicate that the proposed solution algorithm is an effective way in the simultaneous identification of aquifer parameters and their corresponding zone structures.
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M. Omidvari
2015-09-01
Full Text Available Introduction: Occupational accidents are of the main issues in industries. It is necessary to identify the main root causes of accidents for their control. Several models have been proposed for determining the accidents root causes. FTA is one of the most widely used models which could graphically establish the root causes of accidents. The non-linear function is one of the main challenges in FTA compliance and in order to obtain the exact number, the meta-heuristic algorithms can be used. Material and Method: The present research was done in power plant industries in construction phase. In this study, a pattern for the analysis of human error in work-related accidents was provided by combination of neural network algorithms and FTA analytical model. Finally, using this pattern, the potential rate of all causes was determined. Result: The results showed that training, age, and non-compliance with safety principals in the workplace were the most important factors influencing human error in the occupational accident. Conclusion: According to the obtained results, it can be concluded that human errors can be greatly reduced by training, right choice of workers with regard to the type of occupations, and provision of appropriate safety conditions in the work place.
Tavakkoli-Moghaddam, Reza; Alinaghian, Mehdi; Salamat-Bakhsh, Alireza; Norouzi, Narges
2012-05-01
A vehicle routing problem is a significant problem that has attracted great attention from researchers in recent years. The main objectives of the vehicle routing problem are to minimize the traveled distance, total traveling time, number of vehicles and cost function of transportation. Reducing these variables leads to decreasing the total cost and increasing the driver's satisfaction level. On the other hand, this satisfaction, which will decrease by increasing the service time, is considered as an important logistic problem for a company. The stochastic time dominated by a probability variable leads to variation of the service time, while it is ignored in classical routing problems. This paper investigates the problem of the increasing service time by using the stochastic time for each tour such that the total traveling time of the vehicles is limited to a specific limit based on a defined probability. Since exact solutions of the vehicle routing problem that belong to the category of NP-hard problems are not practical in a large scale, a hybrid algorithm based on simulated annealing with genetic operators was proposed to obtain an efficient solution with reasonable computational cost and time. Finally, for some small cases, the related results of the proposed algorithm were compared with results obtained by the Lingo 8 software. The obtained results indicate the efficiency of the proposed hybrid simulated annealing algorithm.
Clement, Bradley J.; Estlin, Tara A.; Bornstein, Benjamin J.
2013-01-01
The Mobile Thread Task Manager (MTTM) is being applied to parallelizing existing flight software to understand the benefits and to develop new techniques and architectural concepts for adapting software to multicore architectures. It allocates and load-balances tasks for a group of threads that migrate across processors to improve cache performance. In order to balance-load across threads, the MTTM augments a basic map-reduce strategy to draw jobs from a global queue. In a multicore processor, memory may be "homed" to the cache of a specific processor and must be accessed from that processor. The MTTB architecture wraps access to data with thread management to move threads to the home processor for that data so that the computation follows the data in an attempt to avoid L2 cache misses. Cache homing is also handled by a memory manager that translates identifiers to processor IDs where the data will be homed (according to rules defined by the user). The user can also specify the number of threads and processors separately, which is important for tuning performance for different patterns of computation and memory access. MTTM efficiently processes tasks in parallel on a multiprocessor computer. It also provides an interface to make it easier to adapt existing software to a multiprocessor environment.
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available We define a special case for the vehicle routing problem with stochastic demands (SC-VRPSD where customer demands are normally distributed. We propose a new linear model for computing the expected length of a tour in SC-VRPSD. The proposed model is based on the integration of the “Traveling Salesman Problem” (TSP and the Assignment Problem. For large-scale problems, we also use an Iterated Local Search (ILS algorithm in order to reach an effective solution.
Model of Wagons’ Placing-In and Taking-Out Problem in a Railway Station and Its Heuristic Algorithm
Directory of Open Access Journals (Sweden)
Chuijiang Guo
2014-01-01
Full Text Available Placing-in and taking-out wagons timely can decrease wagons’ dwell time in railway stations, improve the efficiency of railway transportation, and reduce the cost of goods transportation. We took the locomotive running times between goods operation sites as weights, so the wagons’ placing-in and taking-out problem could be regarded as a single machine scheduling problem, 1pijCmax, which could be transformed into the shortest circle problem in a Hamilton graph whose relaxation problem was an assignment problem. We used a Hungarian algorithm to calculate the optimal solution of the assignment problem. Then we applied a broken circle and connection method, whose computational complexity was O(n2, to find the available satisfactory order of wagons’ placing-in and taking-out. Complex problems, such as placing-in and transferring combined, taking-out and transferring combined, placing-in and taking-out combined, or placing-in, transferring, and taking-out combined, could also be resolved with the extended algorithm. A representative instance was given to illustrate the reliability and efficiency of our results.
Jough, Fooad Karimi Ghaleh; Şensoy, Serhan
2016-12-01
Different performance levels may be obtained for sideway collapse evaluation of steel moment frames depending on the evaluation procedure used to handle uncertainties. In this article, the process of representing modelling uncertainties, record to record (RTR) variations and cognitive uncertainties for moment resisting steel frames of various heights is discussed in detail. RTR uncertainty is used by incremental dynamic analysis (IDA), modelling uncertainties are considered through backbone curves and hysteresis loops of component, and cognitive uncertainty is presented in three levels of material quality. IDA is used to evaluate RTR uncertainty based on strong ground motion records selected by the k-means algorithm, which is favoured over Monte Carlo selection due to its time saving appeal. Analytical equations of the Response Surface Method are obtained through IDA results by the Cuckoo algorithm, which predicts the mean and standard deviation of the collapse fragility curve. The Takagi-Sugeno-Kang model is used to represent material quality based on the response surface coefficients. Finally, collapse fragility curves with the various sources of uncertainties mentioned are derived through a large number of material quality values and meta variables inferred by the Takagi-Sugeno-Kang fuzzy model based on response surface method coefficients. It is concluded that a better risk management strategy in countries where material quality control is weak, is to account for cognitive uncertainties in fragility curves and the mean annual frequency.
Directory of Open Access Journals (Sweden)
Eric Z. Chen
2015-01-01
Full Text Available Error control codes have been widely used in data communications and storage systems. One central problem in coding theory is to optimize the parameters of a linear code and construct codes with best possible parameters. There are tables of best-known linear codes over finite fields of sizes up to 9. Recently, there has been a growing interest in codes over $\\mathbb{F}_{13}$ and other fields of size greater than 9. The main purpose of this work is to present a database of best-known linear codes over the field $\\mathbb{F}_{13}$ together with upper bounds on the minimum distances. To find good linear codes to establish lower bounds on minimum distances, an iterative heuristic computer search algorithm is employed to construct quasi-twisted (QT codes over the field $\\mathbb{F}_{13}$ with high minimum distances. A large number of new linear codes have been found, improving previously best-known results. Tables of $[pm, m]$ QT codes over $\\mathbb{F}_{13}$ with best-known minimum distances as well as a table of lower and upper bounds on the minimum distances for linear codes of length up to 150 and dimension up to 6 are presented.
RELAXATION HEURISTICS FOR THE SET COVERING PROBLEM
Umetani, Shunji; Yagiura, Mutsunori; 柳浦, 睦憲
2007-01-01
The set covering problem (SCP) is one of representative combinatorial optimization problems, which has many practical applications. The continuous development of mathematical programming has derived a number of impressive heuristic algorithms as well as exact branch-and-bound algorithms, which can solve huge SCP instances of bus, railway and airline crew scheduling problems. We survey heuristic algorithms for SCP focusing mainly on contributions of mathematical programming techniques to heuri...
Directory of Open Access Journals (Sweden)
Fanrong Kong
2017-09-01
Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.
2015-01-01
How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the ‘method’ of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself? The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.
Energy Technology Data Exchange (ETDEWEB)
Chiu, George L.; Eichenberger, Alexandre E.; O' Brien, John K. P.
2016-12-13
The present disclosure relates generally to a dedicated memory structure (that is, hardware device) holding data for detecting available worker thread(s) and informing available worker thread(s) of task(s) to execute.
Energy Technology Data Exchange (ETDEWEB)
Delbem, Alexandre C.B.; Bretas, Newton G. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Engenharia Eletrica; Carvalho, Andre C.P.L.F. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Ciencias de Computacao e Estatistica
1996-11-01
A search approach using fuzzy heuristics and a neural network parameter was developed for service restoration of a distribution system. The goal was to restore energy for an un-faulted zone after a fault had been identified and isolated. The restoration plan must be carried out in a very short period. However, the combinatorial feature of the problem constrained the application of automatic energy restoration planners. To overcome this problem, an heuristic search approach using fuzzy heuristics was proposed. As a result, a genetic algorithm approach was developed to achieve the optimal energy restoration plan. The effectiveness of these approaches were tested in a simplified distribution system based on the complex distribution system of Sao Carlos city, Sao Paulo State - southeast Brazil. It was noticed that the genetic algorithm provided better performance than the fuzzy heuristic search in this problem. 11 refs., 10 figs.
Comparison of Heuristics for Inhibitory Rule Optimization
Alsolami, Fawaz; Chikalov, Igor; Moshkov, Mikhail
2014-01-01
Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.
Comparison of Heuristics for Inhibitory Rule Optimization
Alsolami, Fawaz
2014-09-13
Knowledge representation and extraction are very important tasks in data mining. In this work, we proposed a variety of rule-based greedy algorithms that able to obtain knowledge contained in a given dataset as a series of inhibitory rules containing an expression “attribute ≠ value” on the right-hand side. The main goal of this paper is to determine based on rule characteristics, rule length and coverage, whether the proposed rule heuristics are statistically significantly different or not; if so, we aim to identify the best performing rule heuristics for minimization of rule length and maximization of rule coverage. Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.
de Jong, Menno D.T.; van der Geest, Thea
2000-01-01
This article is intended to make Web designers more aware of the qualities of heuristics by presenting a framework for analyzing the characteristics of heuristics. The framework is meant to support Web designers in choosing among alternative heuristics. We hope that better knowledge of the
Bolt Thread Stress Optimization
DEFF Research Database (Denmark)
Pedersen, Niels Leergaard
2012-01-01
of threads and therefore indirectly the bolt fatigue life. The root shape is circular, and from shape optimization for minimum stress concentration it is well known that the circular shape is seldom optimal. An axisymmetric Finite Element (FE) formulation is used to analyze the bolted connection, and a study...... is performed to establish the need for contact modeling with regard to finding the correct stress concentration factor. Optimization is performed with a simple parameterization with two design variables. Stress reduction of up to 9% is found in the optimization process, and some similarities are found...... in the optimized designs leading to the proposal of a new standard. The reductions in the stress are achieved by rather simple changes made to the cutting tool....
A general heuristic for genome rearrangement problems.
Dias, Ulisses; Galvão, Gustavo Rodrigues; Lintzmayer, Carla Négri; Dias, Zanoni
2014-06-01
In this paper, we present a general heuristic for several problems in the genome rearrangement field. Our heuristic does not solve any problem directly, it is rather used to improve the solutions provided by any non-optimal algorithm that solve them. Therefore, we have implemented several algorithms described in the literature and several algorithms developed by ourselves. As a whole, we implemented 23 algorithms for 9 well known problems in the genome rearrangement field. A total of 13 algorithms were implemented for problems that use the notions of prefix and suffix operations. In addition, we worked on 5 algorithms for the classic problem of sorting by transposition and we conclude the experiments by presenting results for 3 approximation algorithms for the sorting by reversals and transpositions problem and 2 approximation algorithms for the sorting by reversals problem. Another algorithm with better approximation ratio can be found for the last genome rearrangement problem, but it is purely theoretical with no practical implementation. The algorithms we implemented in addition to our heuristic lead to the best practical results in each case. In particular, we were able to improve results on the sorting by transpositions problem, which is a very special case because many efforts have been made to generate algorithms with good results in practice and some of these algorithms provide results that equal the optimum solutions in many cases. Our source codes and benchmarks are freely available upon request from the authors so that it will be easier to compare new approaches against our results.
Heuristic approach to Satellite Range Scheduling with Bounds using Lagrangian Relaxation.
Energy Technology Data Exchange (ETDEWEB)
Brown, Nathanael J. K.; Arguello, Bryan; Nozick, Linda Karen; Xu, Ningxiong [Cornell
2017-03-01
This paper focuses on scheduling antennas to track satellites using a heuristic method. In order to validate the performance of the heuristic, bounds are developed using Lagrangian relaxation. The performance of the algorithm is established using several illustrative problems.
Gigerenzer, Gerd; Gaissmaier, Wolfgang
2011-01-01
As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.
Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin
2016-03-01
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
Heuristics for no-wait flow shop scheduling problem
Directory of Open Access Journals (Sweden)
Kewal Krishan Nailwal
2016-09-01
Full Text Available No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard’s benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard’s instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.
Heuristics Miner for E-Commerce Visitor Access Pattern Representation
Kartina Diah Kesuma Wardhani; Wawan Yunanto
2017-01-01
E-commerce click stream data can form a certain pattern that describe visitor behavior while surfing the e-commerce website. This pattern can be used to initiate a design to determine alternative access sequence on the website. This research use heuristic miner algorithm to determine the pattern. σ-Algorithm and Genetic Mining are methods used for pattern recognition with frequent sequence item set approach. Heuristic Miner is an evolved form of those methods. σ-Algorithm assume that an activ...
Multi-threaded software framework development for the ATLAS experiment
AUTHOR|(INSPIRE)INSPIRE-00226135; Baines, John; Bold, Tomasz; Calafiura, Paolo; Dotti, Andrea; Farrell, Steven; Leggett, Charles; Malon, David; Ritsch, Elmar; Snyder, Scott; Tsulaia, Vakhtang; van Gemmeren, Peter; Wynne, Benjamin
2016-01-01
ATLAS's current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognised for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. ATLAS examined the requirements on an updated multi-threaded framework and laid out plans for a new framework, including better support for high level trigger (HLT) use cases, in 2014. In this paper we report on our progress in developing the new multi-threaded task parallel extension of Athena, AthenaMT. Implementing AthenaMT has required many significant code changes. Progress has been made in updating key concepts of the framework, to allow the incorporation of different levels of thread safety in algorithmic code (from un-migrated thread-unsafe code, to thread safe copyable code to reentrant co...
Multi-threaded Software Framework Development for the ATLAS Experiment
Stewart, Graeme; The ATLAS collaboration; Baines, John; Calafiura, Paolo; Dotti, Andrea; Farrell, Steven; Leggett, Charles; Malon, David; Ritsch, Elmar; Snyder, Scott; Tsulaia, Vakhtang; van Gemmeren, Peter; Wynne, Benjamin
2016-01-01
ATLAS's current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognised for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. ATLAS examined the requirements on an updated multi-threaded framework and layed out plans for a new framework, including better support for high level trigger (HLT) use cases, in 2014. In this paper we report on our progress in developing the new multi-threaded task parallel extension of Athena, AthenaMT. Implementing AthenaMT has required many significant code changes. Progress has been made in updating key concepts of the framework, to allow the incorporation of different levels of thread safety in algorithmic code (from un-migrated thread-unsafe code, to thread safe copyable code to reentrant c...
Directory of Open Access Journals (Sweden)
I PUTU SUDANA
2011-01-01
Full Text Available Prinsip heuristics tidak dapat dikatakan sebagai sebuah pendekatanpengambilan keputusan yang non-rasional, karena penerapan atau penggunaanyang unconscious atau subtle mind tidak dapat dianggap sebagai tindakanyang irrational. Dengan alasan tersebut, terdapat cukup alasan untukmenyatakan bahwa pengklasifikasian pendekatan-pendekatan keputusansemestinya menggunakan terminologi analytical dan experiential, dan bukanmemakai istilah rational dan non-rational seperti yang umumnya diikuti.Penerapan pendekatan heuristics dapat ditemukan pada berbagai disiplin,termasuk bisnis dan akuntansi. Topik heuristics semestinya mendapatperhatian yang cukup luas dari para periset di bidang akuntansi. Bidangbehavioral research in accounting menawarkan banyak kemungkinan untukdikaji, karena prinsip heuristics bertautan erat dengan aspek manusia sebagaipelaku dalam pengambilan keputusan.
Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K.
2012-01-01
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system's size. © 2006 IEEE.
Klingbeil, Guido
2012-02-01
We explore two different threading approaches on a graphics processing unit (GPU) exploiting two different characteristics of the current GPU architecture. The fat thread approach tries to minimize data access time by relying on shared memory and registers potentially sacrificing parallelism. The thin thread approach maximizes parallelism and tries to hide access latencies. We apply these two approaches to the parallel stochastic simulation of chemical reaction systems using the stochastic simulation algorithm (SSA) by Gillespie [14]. In these cases, the proposed thin thread approach shows comparable performance while eliminating the limitation of the reaction system\\'s size. © 2006 IEEE.
Effective verification of confidentiality for multi-threaded programs
Ngo, Minh Tri; Stoelinga, Mariëlle Ida Antoinette; Huisman, Marieke
2014-01-01
This paper studies how confidentiality properties of multi-threaded programs can be verified efficiently by a combination of newly developed and existing model checking algorithms. In particular, we study the verification of scheduler-specific observational determinism (SSOD), a property that
Optimization of bolt thread stress concentrations
DEFF Research Database (Denmark)
Pedersen, Niels Leergaard
2013-01-01
Designs of threaded fasteners are controlled by different standards, and the number of different thread definitions is large. The most commonly used thread is probably the metric ISO thread, and this design is therefore used in the present paper. Thread root design controls the stress concentration...... are found in the optimized designs leading to the proposal of a new standard. The reductions in the stress are achieved by rather simple changes made to the cutting tool....
Heuristic thinking makes a chemist smart.
Graulich, Nicole; Hopf, Henning; Schreiner, Peter R
2010-05-01
We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.
Heuristics as Bayesian inference under extreme priors.
Parpart, Paula; Jones, Matt; Love, Bradley C
2018-05-01
Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Hyper-heuristics with low level parameter adaptation.
Ren, Zhilei; Jiang, He; Xuan, Jifeng; Luo, Zhongxuan
2012-01-01
Recent years have witnessed the great success of hyper-heuristics applying to numerous real-world applications. Hyper-heuristics raise the generality of search methodologies by manipulating a set of low level heuristics (LLHs) to solve problems, and aim to automate the algorithm design process. However, those LLHs are usually parameterized, which may contradict the domain independent motivation of hyper-heuristics. In this paper, we show how to automatically maintain low level parameters (LLPs) using a hyper-heuristic with LLP adaptation (AD-HH), and exemplify the feasibility of AD-HH by adaptively maintaining the LLPs for two hyper-heuristic models. Furthermore, aiming at tackling the search space expansion due to the LLP adaptation, we apply a heuristic space reduction (SAR) mechanism to improve the AD-HH framework. The integration of the LLP adaptation and the SAR mechanism is able to explore the heuristic space more effectively and efficiently. To evaluate the performance of the proposed algorithms, we choose the p-median problem as a case study. The empirical results show that with the adaptation of the LLPs and the SAR mechanism, the proposed algorithms are able to achieve competitive results over the three heterogeneous classes of benchmark instances.
Intelligent System Design Using Hyper-Heuristics
Directory of Open Access Journals (Sweden)
Nelishia Pillay
2015-07-01
Full Text Available Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be sufficient and hybridization of methods may be needed to find a solution. This process can be time consuming. The paper proposes the use of hyper-heuristics as a means of identifying which method or combination of approaches is needed to solve a problem. The research presented forms part of a larger initiative aimed at using hyper-heuristics to develop intelligent hybrid systems. As an initial step in this direction, this paper investigates this for classical artificial intelligence uninformed and informed search methods, namely depth first search, breadth first search, best first search, hill-climbing and the A* algorithm. The hyper-heuristic determines the search or combination of searches to use to solve the problem. An evolutionary algorithm hyper-heuristic is implemented for this purpose and its performance is evaluated in solving the 8-Puzzle, Towers of Hanoi and Blocks World problems. The hyper-heuristic employs a generational evolutionary algorithm which iteratively refines an initial population using tournament selection to select parents, which the mutation and crossover operators are applied to for regeneration. The hyper-heuristic was able to identify a search or combination of searches to produce solutions for the twenty 8-Puzzle, five Towers of Hanoi and five Blocks World problems. Furthermore, admissible solutions were produced for all problem instances.
Development of Thread-compatible Open Source Stack
Zimmermann, Lukas; Mars, Nidhal; Schappacher, Manuel; Sikora, Axel
2017-07-01
The Thread protocol is a recent development based on 6LoWPAN (IPv6 over IEEE 802.15.4), but with extensions regarding a more media independent approach, which - additionally - also promises true interoperability. To evaluate and analyse the operation of a Thread network a given open source 6LoWPAN stack for embedded devices (emb::6) has been extended in order to comply with the Thread specification. The implementation covers Mesh Link Establishment (MLE) and network layer functionality as well as 6LoWPAN mesh under routing mechanism based on MAC short addresses. The development has been verified on a virtualization platform and allows dynamical establishment of network topologies based on Thread’s partitioning algorithm.
DEFF Research Database (Denmark)
Sousa, Tiago; Morais, Hugo; Castro, Rui
2016-01-01
vehicles. The proposed algorithms proved to present results very close to the optimal with a small difference between 0.1%. A deterministic technique is used as comparison and it took around 26 h to obtain the optimal one. On the other hand, the simulated annealing was able of obtaining results around 1...
Pitfalls in Teaching Judgment Heuristics
Shepperd, James A.; Koch, Erika J.
2005-01-01
Demonstrations of judgment heuristics typically focus on how heuristics can lead to poor judgments. However, exclusive focus on the negative consequences of heuristics can prove problematic. We illustrate the problem with the representativeness heuristic and present a study (N = 45) that examined how examples influence understanding of the…
Indian Academy of Sciences (India)
polynomial) division 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.
Efficient heuristics for maximum common substructure search.
Englert, Péter; Kovács, Péter
2015-05-26
Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.
International Nuclear Information System (INIS)
Kauffman, L.H.
1990-01-01
This paper gives a heuristic derivation of the skein relation for the Homfly polynomial in an integral formalism. The derivation is formally correct but highly simplified. In the light of Witten's proposal for invariants of links via functional integrals, it is useful to have a formal pattern to compare with the complexities of the full approach. The formalism is a heuristic. However, it is closely related to the actual structure of the Witten functional integral
Using tree diversity to compare phylogenetic heuristics.
Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L
2009-04-29
Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees-especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest.
Impact of heuristics in clustering large biological networks.
Shafin, Md Kishwar; Kabir, Kazi Lutful; Ridwan, Iffatur; Anannya, Tasmiah Tamzid; Karim, Rashid Saadman; Hoque, Mohammad Mozammel; Rahman, M Sohel
2015-12-01
Traditional clustering algorithms often exhibit poor performance for large networks. On the contrary, greedy algorithms are found to be relatively efficient while uncovering functional modules from large biological networks. The quality of the clusters produced by these greedy techniques largely depends on the underlying heuristics employed. Different heuristics based on different attributes and properties perform differently in terms of the quality of the clusters produced. This motivates us to design new heuristics for clustering large networks. In this paper, we have proposed two new heuristics and analyzed the performance thereof after incorporating those with three different combinations in a recently celebrated greedy clustering algorithm named SPICi. We have extensively analyzed the effectiveness of these new variants. The results are found to be promising. Copyright © 2015 Elsevier Ltd. All rights reserved.
Thread Structure: Rewriting the Hollywood Formula.
Smith, Evan
2000-01-01
Describes a new nonlinear model that has crept into Hollywood's cinematic repertoire in which multiple story threads comprise the story. Examines how this thread structure differs from ensemble stories. Examines differences between traditionally linear films and films with thread structure regarding character roles and viewer orientation, shifts…
Directory of Open Access Journals (Sweden)
Jianzhong Zhou
2018-04-01
Full Text Available With the fast development of artificial intelligence techniques, data-driven modeling approaches are becoming hotspots in both academic research and engineering practice. This paper proposes a novel data-driven T-S fuzzy model to precisely describe the complicated dynamic behaviors of pumped storage generator motor (PSGM. In premise fuzzy partition of the proposed T-S fuzzy model, a novel variable-length tree-seed algorithm based competitive agglomeration (VTSA-CA algorithm is presented to determine the optimal number of clusters automatically and improve the fuzzy clustering performances. Besides, in order to promote modeling accuracy of PSGM, the input and output formats in the T-S fuzzy model are selected by an economical parameter controlled auto-regressive (CAR model derived from a high-order transfer function of PSGM considering the distributed components in the water diversion system of the power plant. The effectiveness and superiority of the T-S fuzzy model for PSGM under different working conditions are validated by performing comparative studies with both practical data and the conventional mechanistic model.
ADVANCED SCHEDULER FOR COOPERATIVE EXECUTION OF THREADS ON MULTI-CORE SYSTEM
Directory of Open Access Journals (Sweden)
O. N. Karasik
2017-01-01
Full Text Available Three architectures of the cooperative thread scheduler in a multithreaded application that is executed on a multi-core system are considered. Architecture A0 is based on the synchronization and scheduling facilities, which are provided by the operating system. Architecture A1 introduces a new synchronization primitive and a single queue of the blocked threads in the scheduler, which reduces the interaction activity between the threads and operating system, and significantly speed up the processes of blocking and unblocking the threads. Architecture A2 replaces the single queue of blocked threads with dedicated queues, one for each of the synchronizing primitives, extends the number of internal states of the primitive, reduces the inter- dependence of the scheduling threads, and further significantly speeds up the processes of blocking and unblocking the threads. All scheduler architectures are implemented on Windows operating systems and based on the User Mode Scheduling. Important experimental results are obtained for multithreaded applications that implement two blocked parallel algorithms of solving the linear algebraic equation systems by the Gaussian elimination. The algorithms differ in the way of the data distribution among threads and by the thread synchronization models. The number of threads varied from 32 to 7936. Architecture A1 shows the acceleration of up to 8.65% and the architecture A2 shows the acceleration of up to 11.98% compared to A0 architecture for the blocked parallel algorithms computing the triangular form and performing the back substitution. On the back substitution stage of the algorithms, architecture A1 gives the acceleration of up to 125%, and architecture A2 gives the acceleration of up to 413% compared to architecture A0. The experiments clearly show that the proposed architectures, A1 and A2 outperform A0 depending on the number of thread blocking and unblocking operations, which happen during the execution of
Advances in heuristic signal processing and applications
Chatterjee, Amitava; Siarry, Patrick
2013-01-01
There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Heuristic approach to train rescheduling
Directory of Open Access Journals (Sweden)
Mladenović Snežana
2007-01-01
Full Text Available Starting from the defined network topology and the timetable assigned beforehand, the paper considers a train rescheduling in respond to disturbances that have occurred. Assuming that the train trips are jobs, which require the elements of infrastructure - resources, it was done by the mapping of the initial problem into a special case of job shop scheduling problem. In order to solve the given problem, a constraint programming approach has been used. A support to fast finding "enough good" schedules is offered by original separation, bound and search heuristic algorithms. In addition, to improve the time performance, instead of the actual objective function with a large domain, a surrogate objective function is used with a smaller domain, if there is such. .
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
TOUR CONSTRUCTION HEURISTICS FOR AN ORDER SEQUENCING PROBLEM
Directory of Open Access Journals (Sweden)
De Villiers, A. P.
2012-11-01
Full Text Available An order picking system that requires pickers to move in a clockwise direction around a picking line with fixed locations is considered. The problem is divided into three tiers. The tier in which orders must be sequenced is addressed. Eight tour construction heuristics are developed and implemented for an order picking system operating in unidirectional picking lines. Two classes of tour construction heuristics the tour construction starting position ( and the tour construction ending position ( are developed to sequence orders in a picking line. All algorithms are tested and compared using real life data sets. The best solution quality was obtained by a heuristic with adaptations.
On the Importance of Elimination Heuristics in Lazy Propagation
DEFF Research Database (Denmark)
Madsen, Anders Læsø; Butz, Cory J.
2012-01-01
elimination orders on-line. This paper considers the importance of elimination heuristics in LP when using Variable Elimination (VE) as the message and single marginal computation algorithm. It considers well-known cost measures for selecting the next variable to eliminate and a new cost measure....... The empirical evaluation examines dierent heuristics as well as sequences of cost measures, and was conducted on real-world and randomly generated Bayesian networks. The results show that for most cases performance is robust relative to the cost measure used and in some cases the elimination heuristic can have...
Heuristics for the economic dispatch problem
Energy Technology Data Exchange (ETDEWEB)
Flores, Benjamin Carpio [Centro Nacional de Controle de Energia (CENACE), Mexico, D.F. (Mexico). Dept. de Planificacion Economica de Largo Plazo], E-mail: benjamin.carpo@cfe.gob.mx; Laureano Cruces, A L; Lopez Bracho, R; Ramirez Rodriguez, J. [Universidad Autonoma Metropolitana (UAM), Mexico, D.F. (Brazil). Dept. de Sistemas], Emails: clc@correo.azc.uam.mx, rlb@correo.azc.uam.mx, jararo@correo.azc.uam.mx
2009-07-01
This paper presents GRASP (Greedy Randomized Adaptive Search Procedure), Simulated Annealing (SAA), Genetic (GA), and Hybrid Genetic (HGA) Algorithms for the economic dispatch problem (EDP), considering non-convex cost functions and dead zones the only restrictions, showing the results obtained. We also present parameter settings that are specifically applicable to the EDP, and a comparative table of results for each heuristic. It is shown that these methods outperform the classical methods without the need to assume convexity of the target function. (author)
Heuristic versus statistical physics approach to optimization problems
International Nuclear Information System (INIS)
Jedrzejek, C.; Cieplinski, L.
1995-01-01
Optimization is a crucial ingredient of many calculation schemes in science and engineering. In this paper we assess several classes of methods: heuristic algorithms, methods directly relying on statistical physics such as the mean-field method and simulated annealing; and Hopfield-type neural networks and genetic algorithms partly related to statistical physics. We perform the analysis for three types of problems: (1) the Travelling Salesman Problem, (2) vector quantization, and (3) traffic control problem in multistage interconnection network. In general, heuristic algorithms perform better (except for genetic algorithms) and much faster but have to be specific for every problem. The key to improving the performance could be to include heuristic features into general purpose statistical physics methods. (author)
Heuristic decision making in medicine
Marewski, Julian N.; Gigerenzer, Gerd
2012-01-01
Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care. PMID:22577307
Heuristic decision making in medicine.
Marewski, Julian N; Gigerenzer, Gerd
2012-03-01
Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care.
A perturbative clustering hyper-heuristic framework for the Danish railway system
DEFF Research Database (Denmark)
M. Pour, Shahrzad; Rasmussen, Kourosh Marjani; Burke, Edmund K.
, we propose a perturbative clustering hyper-heuristic framework. The framework improves an initial solution by reassigning outliers (those tasks that are far away) to a better cluster choice at each iteration while taking balanced crews workloads into account. The framework introduces five lowlevel...... heuristics and employs an adaptive choice function as a robust learning mechanism. The results of adaptive clustering hyper-heuristic are compared with two exact and heuristic assignment algorithms from the literature and with the random hyper-heuristic framework on 12 datasets. In comparison with the exact...... formulation, the proposed framework could obtain promising results and solved the data instances up to 5000 number of tasks. In comparison with heuristic assignment and the random hyper-heuristic, the framework yielded approximately 11%, 27% and 10%,13% mprovement on total distance and the maximum distance...
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Heuristics in Conflict Resolution
Drescher, Christian; Gebser, Martin; Kaufmann, Benjamin; Schaub, Torsten
2010-01-01
Modern solvers for Boolean Satisfiability (SAT) and Answer Set Programming (ASP) are based on sophisticated Boolean constraint solving techniques. In both areas, conflict-driven learning and related techniques constitute key features whose application is enabled by conflict analysis. Although various conflict analysis schemes have been proposed, implemented, and studied both theoretically and practically in the SAT area, the heuristic aspects involved in conflict analysis have not yet receive...
a new meta-heuristic optimization algorithm
Indian Academy of Sciences (India)
N Archana
programming obtain optimal solution to the problem by rigorous methods supplemented by gradient information. Classical methods are good for solving problems with only ... ronment for their survival and apply the concepts in finding.
Adaptive control in multi-threaded iterated integration
International Nuclear Information System (INIS)
Doncker, Elise de; Yuasa, Fukuko
2013-01-01
In recent years we have developed a technique for the direct computation of Feynman loop-integrals, which are notorious for the occurrence of integrand singularities. Especially for handling singularities in the interior of the domain, we approximate the iterated integral using an adaptive algorithm in the coordinate directions. We present a novel multi-core parallelization scheme for adaptive multivariate integration, by assigning threads to the rule evaluations in the outer dimensions of the iterated integral. The method ensures a large parallel granularity as each function evaluation by itself comprises an integral over the lower dimensions, while the application of the threads is governed by the adaptive control in the outer level. We give computational results for a test set of 3- to 6-dimensional integrals, where several problems exhibit a loop integral behavior.
A Comparison of Genetic Programming Variants for Hyper-Heuristics
Energy Technology Data Exchange (ETDEWEB)
Harris, Sean [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-03-01
Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance in Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.
A New Modified Firefly Algorithm
Directory of Open Access Journals (Sweden)
Medha Gupta
2016-07-01
Full Text Available Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. Firefly Algorithm is one of the new such swarm-based metaheuristic algorithm inspired by the flashing behavior of fireflies. The algorithm was first proposed in 2008 and since then has been successfully used for solving various optimization problems. In this work, we intend to propose a new modified version of Firefly algorithm (MoFA and later its performance is compared with the standard firefly algorithm along with various other meta-heuristic algorithms. Numerical studies and results demonstrate that the proposed algorithm is superior to existing algorithms.
Hair-Thread Tourniquet Syndrome
Directory of Open Access Journals (Sweden)
Emre Gokcen
2016-01-01
Two month-old male infant was brought to the emergency service with the complaint of fever, uneasiness, and swelling on 4th-5th toes of right foot. Apparent swelling, rubescence and increase in heat were seen and a constrictive band was observed to surround proximal phalanges of both toes in the physical examination of the patient (Figure 1. A hair was found on the constrictive band surrounding both toes. The hair was removed by means of forceps. Oral antibiotic was administered to the patient. The patient was treated successfully by not letting a necrosis develop on the toes. It should be remembered that hair-thread tourniquet syndrome may be observed in the infant patients applying to the hospital with the complaints of unexplained fever and uneasiness. Figure 1: Appearance of the toes right after the hair was removed. Arrows show the constrictive band.
Hierarchical resilience with lightweight threads
International Nuclear Information System (INIS)
Wheeler, Kyle Bruce
2011-01-01
This paper proposes methodology for providing robustness and resilience for a highly threaded distributed- and shared-memory environment based on well-defined inputs and outputs to lightweight tasks. These inputs and outputs form a failure 'barrier', allowing tasks to be restarted or duplicated as necessary. These barriers must be expanded based on task behavior, such as communication between tasks, but do not prohibit any given behavior. One of the trends in high-performance computing codes seems to be a trend toward self-contained functions that mimic functional programming. Software designers are trending toward a model of software design where their core functions are specified in side-effect free or low-side-effect ways, wherein the inputs and outputs of the functions are well-defined. This provides the ability to copy the inputs to wherever they need to be - whether that's the other side of the PCI bus or the other side of the network - do work on that input using local memory, and then copy the outputs back (as needed). This design pattern is popular among new distributed threading environment designs. Such designs include the Barcelona STARS system, distributed OpenMP systems, the Habanero-C and Habanero-Java systems from Vivek Sarkar at Rice University, the HPX/ParalleX model from LSU, as well as our own Scalable Parallel Runtime effort (SPR) and the Trilinos stateless kernels. This design pattern is also shared by CUDA and several OpenMP extensions for GPU-type accelerators (e.g. the PGI OpenMP extensions).
Visual thread quality for precision miniature mechanisms
Energy Technology Data Exchange (ETDEWEB)
Gillespie, L.K.
1981-04-01
Threaded features have eight visual appearance factors which can affect their function in precision miniature mechanisms. The Bendix practice in deburring, finishing, and accepting these conditions on miniature threads is described as is their impact in assemblies of precision miniature electromechanical assemblies.
Thread-Skip: An Undefined Common Observation.
McDermott, Peter; Allan, William DE
When a screw-retained implant prosthesis is removed, a click is heard and a slight axial shift is felt, indicating the screw has been fully removed from the retaining thread. This common observation has never been described in the literature. This article describes the click, and it is proposed it be termed thread-skip.
A System for Automatically Generating Scheduling Heuristics
Morris, Robert
1996-01-01
The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.
Theory of Randomized Search Heuristics in Combinatorial Optimization
DEFF Research Database (Denmark)
The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS), the Metr......The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS...... analysis of randomized algorithms to RSHs. Mostly, the expected runtime of RSHs on selected problems is analzyed. Thereby, we understand why and when RSHs are efficient optimizers and, conversely, when they cannot be efficient. The tutorial will give an overview on the analysis of RSHs for solving...
Combined heuristic with fuzzy system to transmission system expansion planning
Energy Technology Data Exchange (ETDEWEB)
Silva Sousa, Aldir; Asada, Eduardo N. [University of Sao Paulo, Sao Carlos School of Engineering, Department of Electrical Engineering Av. Trabalhador Sao-carlense, 400, 13566-590 Sao Carlos, SP (Brazil)
2011-01-15
A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (author)
Why Is There a Glass Ceiling for Threading Based Protein Structure Prediction Methods?
Skolnick, Jeffrey; Zhou, Hongyi
2017-04-20
Despite their different implementations, comparison of the best threading approaches to the prediction of evolutionary distant protein structures reveals that they tend to succeed or fail on the same protein targets. This is true despite the fact that the structural template library has good templates for all cases. Thus, a key question is why are certain protein structures threadable while others are not. Comparison with threading results on a set of artificial sequences selected for stability further argues that the failure of threading is due to the nature of the protein structures themselves. Using a new contact map based alignment algorithm, we demonstrate that certain folds are highly degenerate in that they can have very similar coarse grained fractions of native contacts aligned and yet differ significantly from the native structure. For threadable proteins, this is not the case. Thus, contemporary threading approaches appear to have reached a plateau, and new approaches to structure prediction are required.
Reasoning by analogy as an aid to heuristic theorem proving.
Kling, R. E.
1972-01-01
When heuristic problem-solving programs are faced with large data bases that contain numbers of facts far in excess of those needed to solve any particular problem, their performance rapidly deteriorates. In this paper, the correspondence between a new unsolved problem and a previously solved analogous problem is computed and invoked to tailor large data bases to manageable sizes. This paper outlines the design of an algorithm for generating and exploiting analogies between theorems posed to a resolution-logic system. These algorithms are believed to be the first computationally feasible development of reasoning by analogy to be applied to heuristic theorem proving.
Heuristic methods for shared backup path protection planning
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2012-01-01
schemes are employed. In contrast to manual intervention, automatic protection schemes such as Shared Backup Path Protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5% was achieved for more than half of the benchmark instances (and a gap of less...
Heuristic methods for single link shared backup path protection
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2014-01-01
schemes are employed. In contrast to manual intervention, automatic protection schemes such as shared backup path protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5 % was achieved for 5 of 7 benchmark instances (and a gap of less than 11 % for the remaining...
Heuristics for Multidimensional Packing Problems
DEFF Research Database (Denmark)
Egeblad, Jens
for a minimum height container required for the items. The main contributions of the thesis are three new heuristics for strip-packing and knapsack packing problems where items are both rectangular and irregular. In the two first papers we describe a heuristic for the multidimensional strip-packing problem...... that is based on a relaxed placement principle. The heuristic starts with a random overlapping placement of items and large container dimensions. From the overlapping placement overlap is reduced iteratively until a non-overlapping placement is found and a new problem is solved with a smaller container size...... of this heuristic are among the best published in the literature both for two- and three-dimensional strip-packing problems for irregular shapes. In the third paper, we introduce a heuristic for two- and three-dimensional rectangular knapsack packing problems. The two-dimensional heuristic uses the sequence pair...
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
A Tutorial on Heuristic Methods
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Werra, D. de; Silver, E.
1980-01-01
In this paper we define a heuristic method as a procedure for solving a well-defined mathematical problem by an intuitive approach in which the structure of the problem can be interpreted and exploited intelligently to obtain a reasonable solution. Issues discussed include: (i) the measurement...... of the quality of a heuristic method, (ii) different types of heuristic procedures, (iii) the interactive role of human beings and (iv) factors that may influence the choice or testing of heuristic methods. A large number of references are included....
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Workflow of the Grover algorithm simulation incorporating CUDA and GPGPU
Lu, Xiangwen; Yuan, Jiabin; Zhang, Weiwei
2013-09-01
The Grover quantum search algorithm, one of only a few representative quantum algorithms, can speed up many classical algorithms that use search heuristics. No true quantum computer has yet been developed. For the present, simulation is one effective means of verifying the search algorithm. In this work, we focus on the simulation workflow using a compute unified device architecture (CUDA). Two simulation workflow schemes are proposed. These schemes combine the characteristics of the Grover algorithm and the parallelism of general-purpose computing on graphics processing units (GPGPU). We also analyzed the optimization of memory space and memory access from this perspective. We implemented four programs on CUDA to evaluate the performance of schemes and optimization. Through experimentation, we analyzed the organization of threads suited to Grover algorithm simulations, compared the storage costs of the four programs, and validated the effectiveness of optimization. Experimental results also showed that the distinguished program on CUDA outperformed the serial program of libquantum on a CPU with a speedup of up to 23 times (12 times on average), depending on the scale of the simulation.
The Advanced Thread-Locking Mechanism
Weiss, Wolfgang
2005-12-01
Locking of threaded members is accomplished by a wide variety of engineering solutions. Generally, in terms of separate locking devices or by built-in locking features such as friction generating means.In regard of space flight vehicles, threaded joints are subject to severe vibration loads during launch, maneuvering, and reentry. This requires fastening systems which are capable to join structural members and attach accessories or equipment in a secure manner. However, manned spacecraft and especially payload components will be subject to installation activity during orbital or interstellar flight maintenance, repair, or mission modification. This, in turn, requires fast separation and engaging of the concerned fasteners, yet providing performance characteristics for high reliable and safe joints.The further described Advanced Thread Locking Mechanism (ATLM) has been developed to combine the merits of both, safe joining technique and a fast installation process. The ATLM uses a freewheel which is securely installed in one part of the threaded member and releasable coupled with the engaged counterpart. While screwing the threaded members together, once coupled, the freewheel will allow free mating of the threaded members including torquing to the desired value. The moment, the pair of threaded fasteners is forced to unscrew (by intended or unintended occurrence of torque in the undoing direction) the freewheel does lock instantly. Disengaging the coupling between the members of the threaded joint takes a separate release action.Owing to the nature of the ATLM, there are a number of design variants ready for implementation.Threaded fasteners in ATLM design are highly recommended for mechanical joints subject to fastening and unfastening during Extra Vehicular Activity (EVA) in course of space flight operations. This is justified through:1. Threaded members mate free running, thus, torque values preset at the wrenching tool are not influenced by varying prevailing
The helical tomotherapy thread effect
International Nuclear Information System (INIS)
Kissick, M.W.; Fenwick, J.; James, J.A.; Jeraj, R.; Kapatoes, J.M.; Keller, H.; Mackie, T.R.; Olivera, G.; Soisson, E.T.
2005-01-01
Inherent to helical tomotherapy is a dose variation pattern that manifests as a 'ripple' (peak-to-trough relative to the average). This ripple is the result of helical beam junctioning, completely unique to helical tomotherapy. Pitch is defined as in helical CT, the couch travel distance for a complete gantry rotation relative to the axial beam width at the axis of rotation. Without scattering or beam divergence, an analytical posing of the problem as a simple integral predicts minima near a pitch of 1/n where n is an integer. A convolution-superposition dose calculator (TomoTherapy, Inc.) included all the physics needed to explore the ripple magnitude versus pitch and beam width. The results of the dose calculator and some benchmark measurements demonstrate that the ripple has sharp minima near p=0.86(1/n). The 0.86 factor is empirical and caused by a beam junctioning of the off-axis dose profiles which differ from the axial profiles as well as a long scatter tail of the profiles at depth. For very strong intensity modulation, the 0.86 factor may vary. The authors propose choosing particular minima pitches or using a second delivery that starts 180 deg off-phase from the first to reduce these ripples: 'Double threading'. For current typical pitches and beam widths, however, this effect is small and not clinically important for most situations. Certain extremely large field or high pitch cases, however, may benefit from mitigation of this effect
Heuristics for Hierarchical Partitioning with Application to Model Checking
DEFF Research Database (Denmark)
Möller, Michael Oliver; Alur, Rajeev
2001-01-01
Given a collection of connected components, it is often desired to cluster together parts of strong correspondence, yielding a hierarchical structure. We address the automation of this process and apply heuristics to battle the combinatorial and computational complexity. We define a cost function...... that captures the quality of a structure relative to the connections and favors shallow structures with a low degree of branching. Finding a structure with minimal cost is NP-complete. We present a greedy polynomial-time algorithm that approximates good solutions incrementally by local evaluation of a heuristic...... function. We argue for a heuristic function based on four criteria: the number of enclosed connections, the number of components, the number of touched connections and the depth of the structure. We report on an application in the context of formal verification, where our algorithm serves as a preprocessor...
Automatic Thread-Level Parallelization in the Chombo AMR Library
Energy Technology Data Exchange (ETDEWEB)
Christen, Matthias; Keen, Noel; Ligocki, Terry; Oliker, Leonid; Shalf, John; Van Straalen, Brian; Williams, Samuel
2011-05-26
The increasing on-chip parallelism has some substantial implications for HPC applications. Currently, hybrid programming models (typically MPI+OpenMP) are employed for mapping software to the hardware in order to leverage the hardware?s architectural features. In this paper, we present an approach that automatically introduces thread level parallelism into Chombo, a parallel adaptive mesh refinement framework for finite difference type PDE solvers. In Chombo, core algorithms are specified in the ChomboFortran, a macro language extension to F77 that is part of the Chombo framework. This domain-specific language forms an already used target language for an automatic migration of the large number of existing algorithms into a hybrid MPI+OpenMP implementation. It also provides access to the auto-tuning methodology that enables tuning certain aspects of an algorithm to hardware characteristics. Performance measurements are presented for a few of the most relevant kernels with respect to a specific application benchmark using this technique as well as benchmark results for the entire application. The kernel benchmarks show that, using auto-tuning, up to a factor of 11 in performance was gained with 4 threads with respect to the serial reference implementation.
Heuristics Reasoning in Diagnostic Judgment.
O'Neill, Eileen S.
1995-01-01
Describes three heuristics--short-cut mental strategies that streamline information--relevant to diagnostic reasoning: accessibility, similarity, and anchoring and adjustment. Analyzes factors thought to influence heuristic reasoning and presents interventions to be tested for nursing practice and education. (JOW)
Reexamining Our Bias against Heuristics
McLaughlin, Kevin; Eva, Kevin W.; Norman, Geoff R.
2014-01-01
Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources…
HEURISTIC APPROACHES FOR PORTFOLIO OPTIMIZATION
Manfred Gilli, Evis Kellezi
2000-01-01
The paper first compares the use of optimization heuristics to the classical optimization techniques for the selection of optimal portfolios. Second, the heuristic approach is applied to problems other than those in the standard mean-variance framework where the classical optimization fails.
The mathematical model of thread unrolling from a bobbin
Directory of Open Access Journals (Sweden)
S. M. Tenenbaum
2014-01-01
Full Text Available I. Introduction The subject of research in this work is a process of thread unrolling from a bobbin. The mathematical model of this process considering motion of thread peace on a bobbin and unrolled peace is proposed. The dimension of system of differential equations for this model is constant during deploying.The relevance to simulate this process for design of Heliogyro-like solar sails (Heliogyro [1], BMSTU-Sail [2] is proved. The paper briefly characterizes a blade for such solar sail as a simulation object. It proves the possibility for using a flexible thread model for a long blade because of very small blade thickness (less than 10 μm [3] relative to blade width and the phenomena of Koriolis forces [4] that lead to buckling failure of blade flatness.The major features of the proposed model are:-- simulated as a motion of the thread piece both being on a bobbin and its unrolled peace;-- splitting a thread length into nodes does not depend on the demand to ensure a sufficient number of nodes on a single thread turn on the coil;-- because of avoiding a problem of contact between the thread and bobbin a stable integration of motion equations is provided by the conventional Runge-Kutta method of fourth order with a constant step [5];-- in the course of solution the number of freedom degrees (number of motion equation is constant, thereby simplifying a calculation algorithm.The closest mathematical model is proposed in [6].The scientific novelty of this research is the approach to solving the problem of unrolling thread from a bobbin using a constant number of motion equations while preserving real kinematics coiling process.II. Problem formulationIn this section the problem of unrolling thread with length L from a bobbin of radius r is posed while any kind of forces are acting on the unrolled peace of thread. Moreover, the law of bobbin rotation φ(t assumed to be known with the proviso that the model can be modified if φ(t is the result of
Optically variable threads and polarization effects
Kretschmar, Friedrich; Burchard, Theodor; Heim, Manfred
2006-02-01
Based on common criteria for efficient security elements for banknotes the set-up of a state-of-the-art holographic security thread is described - as first representative of window embedded OVD. We continue with new colour-shifting OVD-threads - based on physical vapour deposition thin-film and liquid crystal technology. These three then form the family of optically variable threads following the same set of requirements for efficiency, durability, service to all authentication levels and economics. In addition to this set of OVD threads we introduce how liquid crystal based phase retarding layer can be used to install new authentication channels for the public use up-to machine authentication. Also we show the perspective how those development can be used to install similar sets of OVD families of foil elements on banknotes.
Penjadwalan Produksi Garment Menggunakan Algoritma Heuristic Pour
Directory of Open Access Journals (Sweden)
Rizal Rachman
2018-04-01
resources efficiently. The basic calculation of Scheduling using Heuristic Pour algorithm. The research stages consist of data collection, standard time calculation, total time calculation based on job, scheduling with company start method, scheduling with Pour Heuristic method. Based on the results of scheduling using Pour Heuristik obtained savings compared with the current company method, so it can be used as an alternative method in scheduling the process of production process in Garment company. Keywords: Production Scheduling, Algorithms, Heuristic Pour.
Modified strip packing heuristics for the rectangular variable-sized bin packing problem
Directory of Open Access Journals (Sweden)
FG Ortmann
2010-06-01
Full Text Available Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP and the variable-sized bin packing problem (VSBPP. A total of 252 strip packing heuristics (and variations thereof from the literature, as well as novel heuristics proposed by the authors, are compared statistically by means of 1170 SPP benchmark instances in order to identify the best heuristics in various classes. A combination of new heuristics with a new sorting method yields the best results. These heuristics are combined with a previous heuristic for the VSBPP by the authors to find good feasible solutions to 1357 VSBPP benchmark instances. This is the largest statistical comparison of algorithms for the SPP and the VSBPP to the best knowledge of the authors.
Conversation Threads Hidden within Email Server Logs
Palus, Sebastian; Kazienko, Przemysław
Email server logs contain records of all email Exchange through this server. Often we would like to analyze those emails not separately but in conversation thread, especially when we need to analyze social network extracted from those email logs. Unfortunately each mail is in different record and those record are not tided to each other in any obvious way. In this paper method for discussion threads extraction was proposed together with experiments on two different data sets - Enron and WrUT..
Directory of Open Access Journals (Sweden)
Honglin Xu
2014-01-01
Full Text Available Loading and contact stress distribution on the thread teeth in tubing and casing premium threaded connections are of great importance for design optimization, pretightening force control, and thread failure prevention. This paper proposes an analytical method based on the elastic mechanics. This is quite different from other papers, which mainly rely on finite element analysis. The differential equation of load distribution on the thread teeth was established according to equal pitch of the engaged thread after deformation and solved by finite difference method. Furthermore, the relation between load acting on each engaged thread and mean contact stress on its load flank is set up based on the geometric description of thread surface. By comparison, this new analytical method with the finite element analysis for a modified API 177.8 mm premium threaded connection is approved. Comparison of the contact stress on the last engaged thread between analytical model and FEM shows that the accuracy of analytical model will decline with the increase of pretightening force after the material enters into plastic deformation. However, the analytical method can meet the needs of engineering to some extent because its relative error is about 6.2%~18.1% for the in-service level of pretightening force.
Joel, Anna-Christin; Kappel, Peter; Adamova, Hana; Baumgartner, Werner; Scholz, Ingo
2015-11-01
Spider silk production has been studied intensively in the last years. However, capture threads of cribellate spiders employ an until now often unnoticed alternative of thread production. This thread in general is highly interesting, as it not only involves a controlled arrangement of three types of threads with one being nano-scale fibres (cribellate fibres), but also a special comb-like structure on the metatarsus of the fourth leg (calamistrum) for its production. We found the cribellate fibres organized as a mat, enclosing two parallel larger fibres (axial fibres) and forming the typical puffy structure of cribellate threads. Mat and axial fibres are punctiform connected to each other between two puffs, presumably by the action of the median spinnerets. However, this connection alone does not lead to the typical puffy shape of a cribellate thread. Removing the calamistrum, we found a functional capture thread still being produced, but the puffy shape of the thread was lost. Therefore, the calamistrum is not necessary for the extraction or combination of fibres, but for further processing of the nano-scale cribellate fibres. Using data from Uloborus plumipes we were able to develop a model of the cribellate thread production, probably universally valid for cribellate spiders. Copyright © 2015 Elsevier Ltd. All rights reserved.
Heuristically improved Bayesian segmentation of brain MR images ...
African Journals Online (AJOL)
Heuristically improved Bayesian segmentation of brain MR images. ... or even the most prevalent task in medical image processing is image segmentation. Among them, brain MR images suffer ... show that our algorithm performs well in comparison with the one implemented in SPM. It can be concluded that incorporating ...
Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift
DEFF Research Database (Denmark)
Lehre, Per Kristian; Witt, Carsten
2014-01-01
Drift analysis is one of the state-of-the-art techniques for the runtime analysis of randomized search heuristics (RSHs) such as evolutionary algorithms (EAs), simulated annealing etc. The vast majority of existing drift theorems yield bounds on the expected value of the hitting time for a target...
The use of meta-heuristics for airport gate assignment
DEFF Research Database (Denmark)
Cheng, Chun-Hung; Ho, Sin C.; Kwan, Cheuk-Lam
2012-01-01
proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport...... are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data....
Paranoid thinking as a heuristic.
Preti, Antonio; Cella, Matteo
2010-08-01
Paranoid thinking can be viewed as a human heuristic used by individuals to deal with uncertainty during stressful situations. Under stress, individuals are likely to emphasize the threatening value of neutral stimuli and increase the reliance on paranoia-based heuristic to interpreter events and guide their decisions. Paranoid thinking can also be activated by stress arising from the possibility of losing a good opportunity; this may result in an abnormal allocation of attentional resources to social agents. A better understanding of the interplay between cognitive heuristics and emotional processes may help to detect situations in which paranoid thinking is likely to exacerbate and improve intervention for individuals with delusional disorders.
Structural Sustainability - Heuristic Approach
Rostański, Krzysztof
2017-10-01
Nowadays, we are faced with a challenge of having to join building structures with elements of nature, which seems to be the paradigm of modern planning and design. The questions arise, however, with reference to the following categories: the leading idea, the relation between elements of nature and buildings, the features of a structure combining such elements and, finally, our perception of this structure. If we consider both the overwhelming globalization and our attempts to preserve local values, the only reasonable solution is to develop naturalistic greenery. It can add its uniqueness to any building and to any developed area. Our holistic model, presented in this paper, contains the above mentioned categories within the scope of naturalism. The model is divided into principles, actions related, and possible effects to be obtained. It provides a useful tool for determining the ways and priorities of our design. Although it is not possible to consider all possible actions and solutions in order to support sustainability in any particular design, we can choose, however, a proper mode for our design according to the local conditions by turning to the heuristic method, which helps to choose priorities and targets. Our approach is an attempt to follow the ways of nature as in the natural environment it is optimal solutions that appear and survive, idealism being the domain of mankind only. We try to describe various natural processes in a manner comprehensible to us, which is always a generalization. Such definitions, however, called artificial by naturalists, are presented as art or the current state of knowledge by artists and engineers. Reality, in fact, is always more complicated than its definitions. The heuristic method demonstrates the way how to optimize our design. It requires that all possible information about the local environment should be gathered, as the more is known, the fewer mistakes are made. Following the unquestionable principles, we can
Hyper-heuristic applied to nuclear reactor core design
International Nuclear Information System (INIS)
Domingos, R P; Platt, G M
2013-01-01
The design of nuclear reactors gives rises to a series of optimization problems because of the need for high efficiency, availability and maintenance of security levels. Gradient-based techniques and linear programming have been applied, as well as genetic algorithms and particle swarm optimization. The nonlinearity, multimodality and lack of knowledge about the problem domain makes de choice of suitable meta-heuristic models particularly challenging. In this work we solve the optimization problem of a nuclear reactor core design through the application of an optimal sequence of meta-heuritics created automatically. This combinatorial optimization model is known as hyper-heuristic.
Heuristic introduction to gravitational waves
International Nuclear Information System (INIS)
Sandberg, V.D.
1982-01-01
The purpose of this article is to provide a rough and somewhat heuristic theoretical background and introduction to gravitational radiation, its generation, and its detection based on Einstein's general theory of relativity
AthenaMT: upgrading the ATLAS software framework for the many-core world with multi-threading
AUTHOR|(INSPIRE)INSPIRE-00100895; The ATLAS collaboration; Baines, John; Bold, Tomasz; Calafiura, Paolo; Farrell, Steven; Malon, David; Ritsch, Elmar; Stewart, Graeme; Snyder, Scott; Tsulaia, Vakhtang; Wynne, Benjamin; van Gemmeren, Peter
2017-01-01
ATLAS’s current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognized for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. After concluding a rigorous requirements phase, where many design components were examined in detail, ATLAS has begun the migration to a new data-flow driven, multi-threaded framework, which enables the simultaneous processing of singleton, thread unsafe legacy Algorithms, cloned Algorithms that execute concurrently in their own threads with different Event contexts, and fully re-entrant, thread safe Algorithms. In this paper we report on the process of modifying the framework to safely process multiple concurrent events in different threads, which entails significant changes in the underlying ha...
AthenaMT: Upgrading the ATLAS Software Framework for the Many-Core World with Multi-Threading
Leggett, Charles; The ATLAS collaboration; Bold, Tomasz; Calafiura, Paolo; Farrell, Steven; Malon, David; Ritsch, Elmar; Stewart, Graeme; Snyder, Scott; Tsulaia, Vakhtang; Wynne, Benjamin; van Gemmeren, Peter
2016-01-01
ATLAS's current software framework, Gaudi/Athena, has been very successful for the experiment in LHC Runs 1 and 2. However, its single threaded design has been recognised for some time to be increasingly problematic as CPUs have increased core counts and decreased available memory per core. Even the multi-process version of Athena, AthenaMP, will not scale to the range of architectures we expect to use beyond Run2. After concluding a rigorous requirements phase, where many design components were examined in detail, ATLAS has begun the migration to a new data-flow driven, multi-threaded framework, which enables the simultaneous processing of singleton, thread unsafe legacy Algorithms, cloned Algorithms that execute concurrently in their own threads with different Event contexts, and fully re-entrant, thread safe Algorithms. In this paper we will report on the process of modifying the framework to safely process multiple concurrent events in different threads, which entails significant changes in the underlying...
Improved Fatigue Performance of Threaded Drillstring Connections by Cold Rolling
Energy Technology Data Exchange (ETDEWEB)
Kristoffersen, Steinar
2002-01-01
The research work presented in this thesis is concerned with analytical, numerical and experimental studies of the effect of cold rolling on the fatigue behaviour of threaded drillstring connections. A comprehensive literature study is made of the various effects on the fatigue behaviour of residual stresses introduced by mechanical deformation of notched components. Some of the effects studied are cyclic hardening behaviour after prestraining, cyclic creep, fatigue initiation in prestrained materials, short cracks and crack growth models including crack closure. Residual stresses were introduced in the surface of a smooth pipe by a rolling device to simulate a cold rolling process and verify the calculated residual stresses by measurements. Strain hardening and contact algorithm of the two bodies were incorporated in the FE analyses. Two significant errors were found in the commercial software package for residual stress evaluation, Restran v. 3.3.2a also called SINT, when using the Schajer method. The Schajer algorithm is the only hole-drilling algorithm without theoretical shortcomings, and is recommended when measuring large residual stress gradients in the depth direction. Using the Schajer method solved by in-house Matlab-routines good agreement between measured residual stress gradients and residual stress gradients from FE analyses was found. Full scale fatigue tests were performed on pipes cut from used drillstrings with notches of similar geometry as threads used in drillstring connections. The simulated threads consisted of four full depth helix notches with runouts at the surface. The pipe threads were cold rolled and fatigue tested in a full-scale four-point rotating bending fatigue testing rig. The test results showed that cold rolling had an effect on the crack initiation period. A major part of the fatigue life was with cracks observed at the notch root, but due to the increased fatigue crack propagation resistance the final fracture initiated at
Heuristic reasoning and relative incompleteness
Treur, J.
1993-01-01
In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional architecture for reasoning systems that perform such heuristic reasoning is introduced, called SIX (for Strategic Interactive eXpert systems). This compositional architecture enables user interaction a...
International Nuclear Information System (INIS)
Sadjadi, Seyed Jafar; Soltani, R.
2009-01-01
We present a heuristic approach to solve a general framework of serial-parallel redundancy problem where the reliability of the system is maximized subject to some general linear constraints. The complexity of the redundancy problem is generally considered to be NP-Hard and the optimal solution is not normally available. Therefore, to evaluate the performance of the proposed method, a hybrid genetic algorithm is also implemented whose parameters are calibrated via Taguchi's robust design method. Then, various test problems are solved and the computational results indicate that the proposed heuristic approach could provide us some promising reliabilities, which are fairly close to optimal solutions in a reasonable amount of time.
Missing IUD Despite Threads at the Cervix
Directory of Open Access Journals (Sweden)
Andrew L. Atkinson
2014-01-01
Full Text Available Today, the intrauterine device (IUD is by far the most popular form of long term reversible contraception in the world. Side effects from the IUD are minimal and complications are rare. Uterine perforation and migration of the IUD outside the uterine cavity are the most serious complications. Physician visualization and/or the patient feeling retrieval threads at the cervical os are confirmation that the IUD has not been expelled or migrated. We present a case of a perforated, intraperitoneal IUD with threads noted at the cervical os. Office removal was not possible using gentle traction on the threads. Multiple imaging and endoscopic modalities were used to try and locate the IUD including pelvic ultrasound, diagnostic hysteroscopy, cystoscopy, and pelvic magnetic resonance imaging (MRI. The studies gave conflicting results on location of the IUD. Ultimately, the missing IUD was removed via laparoscopy.
Environmentally acceptable thread compounds: Requirements defined
International Nuclear Information System (INIS)
Stringfellow, W.D.; Hendriks, R.V.; Jacobs, N.L.
1993-01-01
New environmental regulations on thread compounds are now being enforced in several areas with strong maritime tradition and a sensitive environment. These areas include Indonesia, Alaska and portions of Norway. The industry generally recognizes the environmental concerns but, with wider enforcement of regulations imminent, has not been able to define clearly the requirements for environmental compliance. This paper, written in collaboration with The Netherlands State Supervision of Mines, is based on the National Policy on Thread Compounds of The Netherlands. This national policy is representative of policies being followed by other North Sea governments. Similar policies might well be adopted by other governments worldwide. These policies will affect the operator, drilling contractor, and supplier. This paper provides a specific and detailed definition of thread compound requirements by addressing four relevant categories. The categories of interest are regulatory approval, environmental, health, and performance
Mathematical models and heuristic solutions for container positioning problems in port terminals
DEFF Research Database (Denmark)
Kallehauge, Louise Sibbesen
2008-01-01
presents an efficient solution algorithm for the CPP. Based on a number of new concepts, an event-based construction heuristic is developed and its ability to solve real-life problem instances is established. The backbone of the algorithm is a list of events, corresponding to a sequence of operations...... by constructing mathematical programming formulations of the problem and developing an efficient heuristic algorithm for its solution. The thesis consists of an introduction, two main chapters concerning new mathematical formulations and a new heuristic for the CPP, technical issues, computational results...... concerning the subject is reviewed. The research presented in this thesis is divided into two main parts: Construction and investigation of new mathematical programming formulations of the CPP and development and implementation of a new event-based heuristic for the problem. The first part presents three...
Multiagent scheduling models and algorithms
Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur
2014-01-01
This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.
Heuristic errors in clinical reasoning.
Rylander, Melanie; Guerrasio, Jeannette
2016-08-01
Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.
Heuristics for minimizing the maximum within-clusters distance
Directory of Open Access Journals (Sweden)
José Augusto Fioruci
2012-12-01
Full Text Available The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at finding a clustering with a predefined number of clusters that minimizes the largest within-cluster distance (diameter among all clusters. There are two main objectives in this paper: to propose heuristics for the MMD and to evaluate the suitability of the best proposed heuristic results according to the real classification of some data sets. Regarding the first objective, the results obtained in the experiments indicate a good performance of the best proposed heuristic that outperformed the Complete Linkage algorithm (the most used method from the literature for this problem. Nevertheless, regarding the suitability of the results according to the real classification of the data sets, the proposed heuristic achieved better quality results than C-Means algorithm, but worse than Complete Linkage.
Practical Formal Verification of MPI and Thread Programs
Gopalakrishnan, Ganesh; Kirby, Robert M.
Large-scale simulation codes in science and engineering are written using the Message Passing Interface (MPI). Shared memory threads are widely used directly, or to implement higher level programming abstractions. Traditional debugging methods for MPI or thread programs are incapable of providing useful formal guarantees about coverage. They get bogged down in the sheer number of interleavings (schedules), often missing shallow bugs. In this tutorial we will introduce two practical formal verification tools: ISP (for MPI C programs) and Inspect (for Pthread C programs). Unlike other formal verification tools, ISP and Inspect run directly on user source codes (much like a debugger). They pursue only the relevant set of process interleavings, using our own customized Dynamic Partial Order Reduction algorithms. For a given test harness, DPOR allows these tools to guarantee the absence of deadlocks, instrumented MPI object leaks and communication races (using ISP), and shared memory races (using Inspect). ISP and Inspect have been used to verify large pieces of code: in excess of 10,000 lines of MPI/C for ISP in under 5 seconds, and about 5,000 lines of Pthread/C code in a few hours (and much faster with the use of a cluster or by exploiting special cases such as symmetry) for Inspect. We will also demonstrate the Microsoft Visual Studio and Eclipse Parallel Tools Platform integrations of ISP (these will be available on the LiveCD).
A communicating Thread -CT- case study: JIWY
Jovanovic, D.S.; Hilderink, G.H.; Broenink, Johannes F.; Pascoe, P.W.J.; Loader, R.; Sunderman, V.
2002-01-01
This JIWY demonstrator is constructed in the context of the development of a design framework and software tools to efficiently support mechatronic engineers in developing sophisticated control computer code out of a set control laws. We use the CSP-based Communicating Threads -CT- library as the
Directory of Open Access Journals (Sweden)
Mário Mestria
2013-08-01
Full Text Available The Clustered Traveling Salesman Problem (CTSP is a generalization of the Traveling Salesman Problem (TSP in which the set of vertices is partitioned into disjoint clusters and objective is to find a minimum cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously. The CTSP is NP-hard and, in this context, we are proposed heuristic methods for the CTSP using GRASP, Path Relinking and Variable Neighborhood Descent (VND. The heuristic methods were tested using Euclidean instances with up to 2000 vertices and clusters varying between 4 to 150 vertices. The computational tests were performed to compare the performance of the heuristic methods with an exact algorithm using the Parallel CPLEX software. The computational results showed that the hybrid heuristic method using VND outperforms other heuristic methods.
Wahid, Juliana; Hussin, Naimah Mohd
2016-08-01
The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution. This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions. The graph heuristics were set as single and combination of two heuristics. In addition, several ways of assigning courses into room and timeslot are implemented. All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced. The result shows that combination of saturation degree followed by largest degree heuristic produce the highest number of population of initial solutions. The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions.
Adaptive switching gravitational search algorithm: an attempt to ...
Indian Academy of Sciences (India)
Nor Azlina Ab Aziz
An adaptive gravitational search algorithm (GSA) that switches between synchronous and ... genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). ...... heuristic with applications in applied electromagnetics. Prog.
Visualization for Hyper-Heuristics: Back-End Processing
Energy Technology Data Exchange (ETDEWEB)
Simon, Luke [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-03-01
Modern society is faced with increasingly complex problems, many of which can be formulated as generate-and-test optimization problems. Yet, general-purpose optimization algorithms may sometimes require too much computational time. In these instances, hyperheuristics may be used. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario, finding the solution significantly faster than its predecessor. However, it may be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics and an easy-to-understand scientific visualization for the produced solutions. To support the development of this GUI, my portion of the research involved developing algorithms that would allow for parsing of the data produced by the hyper-heuristics. This data would then be sent to the front-end, where it would be displayed to the end user.
CPC: programming with a massive number of lightweight threads
Kerneis, Gabriel; Chroboczek, Juliusz
2011-01-01
To appear in PLACES'11.; International audience; Threads are a convenient and modular abstraction for writing concurrent programs, but often fairly expensive. The standard alternative to threads, event-loop programming, allows much lighter units of concurrency, but leads to code that is difficult to write and even harder to understand. Continuation Passing C (CPC) is a translator that converts a program written in threaded style into a program written with events and native system threads, at...
Heuristic Search Theory and Applications
Edelkamp, Stefan
2011-01-01
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constra
Threaded Cognition: An Integrated Theory of Concurrent Multitasking
Salvucci, Dario D.; Taatgen, Niels A.
2008-01-01
The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking--that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed across other available resources (e.g., perceptual…
Threaded cognition : An integrated theory of concurrent multitasking
Salvucci, Dario D.; Taatgen, Niels A.
The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking-that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed
The effect of thread pattern upon implant osseointegration.
Abuhussein, Heba; Pagni, Giorgio; Rebaudi, Alberto; Wang, Hom-Lay
2010-02-01
Implant design features such as macro- and micro-design may influence overall implant success. Limited information is currently available. Therefore, it is the purpose of this paper to examine these factors such as thread pitch, thread geometry, helix angle, thread depth and width as well as implant crestal module may affect implant stability. A literature search was conducted using MEDLINE to identify studies, from simulated laboratory models, animal, to human, related to this topic using the keywords of implant thread, implant macrodesign, thread pitch, thread geometry, helix angle, thread depth, thread width and implant crestal module. The results showed how thread geometry affects the distribution of stress forces around the implant. A decreased thread pitch may positively influence implant stability. Excess helix angles in spite of a faster insertion may jeopardize the ability of implants to sustain axial load. Deeper threads seem to have an important effect on the stabilization in poorer bone quality situations. The addition of threads or microthreads up to the crestal module of an implant might provide a potential positive contribution on bone-to to-implant contact as well as on the preservation of marginal bone; nonetheless this remains to be determined. Appraising the current literature on this subject and combining existing data to verify the presence of any association between the selected characteristics may be critical in the achievement of overall implant success.
Ali, Yasser Helmy
2018-02-01
Thread-lifting rejuvenation procedures have evolved again, with the development of absorbable threads. Although they have gained popularity among plastic surgeons and dermatologists, very few articles have been written in literature about absorbable threads. This study aims to evaluate two years' outcome of thread lifting using absorbable barbed threads for facial rejuvenation. Prospective comparative stud both objectively and subjectively and follow-up assessment for 24 months. Thread lifting for face rejuvenation has significant long-lasting effects that include skin lifting from 3-10 mm and high degree of patients' satisfaction with less incidence rate of complications, about 4.8%. Augmented results are obtained when thread lifting is combined with other lifting and rejuvenation modalities. Significant facial rejuvenation is achieved by thread lifting and highly augmented results are observed when they are combined with Botox, fillers, and/or platelet rich plasma (PRP) rejuvenations.
A Comparison of Heuristics with Modularity Maximization Objective using Biological Data Sets
Directory of Open Access Journals (Sweden)
Pirim Harun
2016-01-01
Full Text Available Finding groups of objects exhibiting similar patterns is an important data analytics task. Many disciplines have their own terminologies such as cluster, group, clique, community etc. defining the similar objects in a set. Adopting the term community, many exact and heuristic algorithms are developed to find the communities of interest in available data sets. Here, three heuristic algorithms to find communities are compared using five gene expression data sets. The heuristics have a common objective function of maximizing the modularity that is a quality measure of a partition and a reflection of objects’ relevance in communities. Partitions generated by the heuristics are compared with the real ones using the adjusted rand index, one of the most commonly used external validation measures. The paper discusses the results of the partitions on the mentioned biological data sets.
A Scalable Heuristic for Viral Marketing Under the Tipping Model
2013-09-01
Flixster is a social media website that allows users to share reviews and other information about cinema . [35] It was extracted in Dec. 2010. – FourSquare...work of Reichman were developed independently . We also note that Reichman performs no experimental evaluation of the algorithm. A Scalable Heuristic...other dif- fusion models, such as the independent cascade model [21] and evolutionary graph theory [25] as well as probabilistic variants of the
A Meta-Heuristic Load Balancer for Cloud Computing Systems
Sliwko, L.; Getov, Vladimir
2015-01-01
This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded ...
Determination of the Tapping Part Diameter of the Thread Mill
Directory of Open Access Journals (Sweden)
A. E. Dreval'
2015-01-01
Full Text Available Currently, there is a tendency to increase the proportion of thread milling operations, among other ways of tapping, which is associated with increasing number of CNC machines, flexibility and versatility of the process.Developments presently existing in the RF and used in the thread mills deal, mainly, with the thread milling cutter designs, to process internal and external thread with straight flutes made from high-speed steel.The paper presents a technique to calculate and select the initial design parameters, i.e. the external diameter of the tapping part of thread milling cutter, which is chosen as a basic computational design. The analysis of directories of tool companies containing foreign de-signs of solid thread end-milling cutters has shown that most of them rep-resent the thread cutter designs made of solid carbide. There are solid and interlocking side milling cutters, which use a tapping part both as a single-disk and as a multi-disk one; chip flutes are made to be both as direct and as screw; solid designs of cutters are made from carbide with a diameter of up to 20 ... 25 mm; thread cutters can be left- and right-hand cutting; Designs of the combined thread mills are proposed; internal channels are used for coolant supply.It is shown that the purpose of the external diameter of the tapping part of the thread mill should take into account the effect of the thread mill diameter on the milling process performance, precision of thread profile received, taper thread, tool strength, and the volume of flutes.The analysis has shown that when choosing the external diameter of the thread mill it worth taking its maximum diameter to improve the char-acteristics of the process under the restrictions imposed on the accuracy of the formed thread.
Heuristic Biases in Mathematical Reasoning
Inglis, Matthew; Simpson, Adrian
2005-01-01
In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…
Heuristic reasoning and relative incompleteness
Treur, J.
1993-01-01
In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional
Heuristic Synthesis of Reversible Logic – A Comparative Study
Directory of Open Access Journals (Sweden)
Chua Shin Cheng
2014-01-01
Full Text Available Reversible logic circuits have been historically motivated by theoretical research in low-power, and recently attracted interest as components of the quantum algorithm, optical computing and nanotechnology. However due to the intrinsic property of reversible logic, traditional irreversible logic design and synthesis methods cannot be carried out. Thus a new set of algorithms are developed correctly to synthesize reversible logic circuit. This paper presents a comprehensive literature review with comparative study on heuristic based reversible logic synthesis. It reviews a range of heuristic based reversible logic synthesis techniques reported by researchers (BDD-based, cycle-based, search-based, non-search-based, rule-based, transformation-based, and ESOP-based. All techniques are described in detail and summarized in a table based on their features, limitation, library used and their consideration metric. Benchmark comparison of gate count and quantum cost are analysed for each synthesis technique. Comparing the synthesis algorithm outputs over the years, it can be observed that different approach has been used for the synthesis of reversible circuit. However, the improvements are not significant. Quantum cost and gate count has improved over the years, but arguments and debates are still on certain issues such as the issue of garbage outputs that remain the same. This paper provides the information of all heuristic based synthesis of reversible logic method proposed over the years. All techniques are explained in detail and thus informative for new reversible logic researchers and bridging the knowledge gap in this area.
Use of barbed threads in facial rejuvenation.
Kalra, Rakesh
2008-10-01
Use of barbed threads, available with uni- and bi-directional cogs or barbs, is a semi-invasive method of lifting sagging skin of the face. Areas treated with this method include the eyebrows, the cheeks, the jowls and the neck. Ease of use and a shorter down-time have made their use popular. Specific indications, operative procedures, risks and complications are described and some clinical results of the author shown.
Use of barbed threads in facial rejuvenation
Directory of Open Access Journals (Sweden)
Kalra Rakesh
2008-10-01
Full Text Available Use of barbed threads, available with uni- and bi-directional cogs or barbs, is a semi-invasive method of lifting sagging skin of the face. Areas treated with this method include the eyebrows, the cheeks, the jowls and the neck. Ease of use and a shorter down-time have made their use popular. Specific indications, operative procedures, risks and complications are described and some clinical results of the author shown.
High efficiency carbon nanotube thread antennas
Amram Bengio, E.; Senic, Damir; Taylor, Lauren W.; Tsentalovich, Dmitri E.; Chen, Peiyu; Holloway, Christopher L.; Babakhani, Aydin; Long, Christian J.; Novotny, David R.; Booth, James C.; Orloff, Nathan D.; Pasquali, Matteo
2017-10-01
Although previous research has explored the underlying theory of high-frequency behavior of carbon nanotubes (CNTs) and CNT bundles for antennas, there is a gap in the literature for direct experimental measurements of radiation efficiency. These measurements are crucial for any practical application of CNT materials in wireless communication. In this letter, we report a measurement technique to accurately characterize the radiation efficiency of λ/4 monopole antennas made from the CNT thread. We measure the highest absolute values of radiation efficiency for CNT antennas of any type, matching that of copper wire. To capture the weight savings, we propose a specific radiation efficiency metric and show that these CNT antennas exceed copper's performance by over an order of magnitude at 1 GHz and 2.4 GHz. We also report direct experimental observation that, contrary to metals, the radiation efficiency of the CNT thread improves significantly at higher frequencies. These results pave the way for practical applications of CNT thread antennas, particularly in the aerospace and wearable electronics industries where weight saving is a priority.
Heuristics for Relevancy Ranking of Earth Dataset Search Results
Lynnes, Christopher; Quinn, Patrick; Norton, James
2016-01-01
As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.
Familiarity and recollection in heuristic decision making.
Schwikert, Shane R; Curran, Tim
2014-12-01
Heuristics involve the ability to utilize memory to make quick judgments by exploiting fundamental cognitive abilities. In the current study we investigated the memory processes that contribute to the recognition heuristic and the fluency heuristic, which are both presumed to capitalize on the byproducts of memory to make quick decisions. In Experiment 1, we used a city-size comparison task while recording event-related potentials (ERPs) to investigate the potential contributions of familiarity and recollection to the 2 heuristics. ERPs were markedly different for recognition heuristic-based decisions and fluency heuristic-based decisions, suggesting a role for familiarity in the recognition heuristic and recollection in the fluency heuristic. In Experiment 2, we coupled the same city-size comparison task with measures of subjective preexperimental memory for each stimulus in the task. Although previous literature suggests the fluency heuristic relies on recognition speed alone, our results suggest differential contributions of recognition speed and recollected knowledge to these decisions, whereas the recognition heuristic relies on familiarity. Based on these results, we created a new theoretical framework that explains decisions attributed to both heuristics based on the underlying memory associated with the choice options. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
Lee, Charles H.; Cheung, Kar-Ming
2012-01-01
In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.
Directory of Open Access Journals (Sweden)
Gregorius Satia Budhi
2002-01-01
Full Text Available The application of Activity Based Costing (ABC approach to select the set-machine that is used in the production of Flexible Manufacture System (FMS based on technical and economical criteria can be useful for producers to design FMS by considering the minimum production cost. In the other hand, Heuristic Search is known to have a short searching time. Algorithm Heuristic that using ABC approach as the weight in finding the solution to shorten the equipment selection time during the design / redesign process of the FMS in less than exponential time was designed in this research. The increasing speed is useful because with the faster time in design / redesign process, therefore the flexibility level of part variety that can be processed will become better. Theoretical and empirical analysis in Algorithm Heuristic shows that time searching to get appropriate set of equipment is not too long, so that we can assume that the designed Algorithm Heuristic can be implemented in the real world. By comparing the empirical result of Algorithm Heuristic to the Algorithm Exhaustive, we can also assume that Algorithm Heuristic that using ABC method as the weight for finding solution can optimise the equipment selection problem of FMS based on economical criteria too. Abstract in Bahasa Indonesia : Penggunaan pendekatan Activity Based Costing (ABC untuk memilih set mesin yang digunakan dalam produksi pada Flexible Manufacture Systems (FMS berdasar atas kriteria teknis dan ekonomis, dapat membantu pelaku produksi untuk mendisain FMS dengan pertimbangan minimalisasi biaya produksi. Sementara itu, Heuristic Search dikenal memiliki waktu pencarian yang singkat. Pada riset ini didisain sebuah Algoritma Heuristic yang menggunakan pendekatan ABC sebagai bobot dalam pencarian solusi, untuk mempersingkat waktu pemilihan peralatan saat desain/redisain FMS dalam waktu kurang dari waktu Eksponensial. Peningkatan kecepatan ini bermanfaat, karena dengan cepatnya waktu
Special relativity a heuristic approach
Hassani, Sadri
2017-01-01
Special Relativity: A Heuristic Approach provides a qualitative exposition of relativity theory on the basis of the constancy of the speed of light. Using Einstein's signal velocity as the defining idea for the notion of simultaneity and the fact that the speed of light is independent of the motion of its source, chapters delve into a qualitative exposition of the relativity of time and length, discuss the time dilation formula using the standard light clock, explore the Minkowski four-dimensional space-time distance based on how the time dilation formula is derived, and define the components of the two-dimensional space-time velocity, amongst other topics. Provides a heuristic derivation of the Minkowski distance formula Uses relativistic photography to see Lorentz transformation and vector algebra manipulation in action Includes worked examples to elucidate and complement the topic being discussed Written in a very accessible style
A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.
Hart, Emma; Sim, Kevin
2016-01-01
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.
APPLICATION PROSPECTS OF THREADED JOINT OF ARMATURE
Directory of Open Access Journals (Sweden)
A. V. Radkevych
2014-06-01
Full Text Available Purpose. One of the main technological operations of buildings construction on the basis of monolithic frame systems is the production of mesh reinforcement. The current interest is the new ways specification of advanced bonding armature techniques without reliability weakness and design of the building in whole, as well as the finding of use prospects of screw-threaded joint of armature as the most technological and economic method of re-bars joints. Methodology. Advantages and disadvantages analysis of existing rebar compound technologies was implemented by couplings of different types and constructions. The most promising vertical constructions for the vertical bars joints in frameworks were determined. Findings. Researches of existing technologies of rebar joints by the couplings of different construction were carried out. The installation method of mesh reinforcement of vertical structural elements with the use of the special catching devices was developed. It allows considerably accelerating installation of mesh reinforcement. Originality. Regularity of labor intensiveness change of mesh reinforcement installation of columns at armature joint in vertical position by threaded couplings with the help of catching devices using special construction was determined. This allows substantially reducing the labor expenditures during installation of these elements. Dependency of labor intensiveness and cost of lap welding armature joints, by tub-seam welding and by thread coupling depending on its diameter was designated. Regularity of labor intensiveness changes of installation at armature joints by different methods taking into account preparatory works was defined. Practical value. The analysis of mechanical armature joints techniques was conducted. It will allow selecting methods of armature joints to increase the speed of construction works more economical and effective.
Pearling Instabilities of a Viscoelastic Thread
Deblais, A.; Velikov, K. P.; Bonn, D.
2018-05-01
Pearling instabilities of slender viscoelastic threads have received much attention, but remain incompletely understood. We study the instabilities in polymer solutions subject to uniaxial elongational flow. Two distinctly different instabilites are observed: beads on a string and blistering. The beads-on-a-string structure arises from a capillary instability whereas the blistering instability has a different origin: it is due to a coupling between stress and polymer concentration. By varying the temperature to change the solution properties we elucidate the interplay between flow and phase separation.
A flow-first route-next heuristic for liner shipping network design
DEFF Research Database (Denmark)
Krogsgaard, Alexander; Pisinger, David; Thorsen, Jesper
2018-01-01
Having a well-designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade-lanes, and reasonable transportation times.The most successful algorithms for liner shipping network design make use of a two-phase approach, where they ﬁrst design the routes...... diﬀerent operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi-commodity ﬂow problem to route the containers through the network, the ﬂow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange...... heuristic for ﬂowing containers is 2–5% from the optimal solution, the solution quality is suﬃciently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to ﬁnd improved solutions for large...
Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.
Nallaperuma, Samadhi; Neumann, Frank; Sudholt, Dirk
2017-01-01
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed-time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1+1) EA and (1+[Formula: see text]) EA algorithms for the TSP in a smoothed complexity setting, and derive the lower bounds of the expected fitness gain for a specified number of generations.
Unified heuristics to solve routing problem of reverse logistics in sustainable supply chain
Anbuudayasankar, S. P.; Ganesh, K.; Lenny Koh, S. C.; Mohandas, K.
2010-03-01
A reverse logistics problem, motivated by many real-life applications, is examined where bottles/cans in which products are delivered from a processing depot to customers in one period are available for return to the depot in the following period. The picked-up bottles/cans need to be adjusted in the place of delivery load. This problem is termed as simultaneous delivery and pick-up problem with constrained capacity (SDPC). We develop three unified heuristics based on extended branch and bound heuristic, genetic algorithm and simulated annealing to solve SDPC. These heuristics are also designed to solve standard travelling salesman problem (TSP) and TSP with simultaneous delivery and pick-up (TSDP). We tested the heuristics on standard, derived and randomly generated datasets of TSP, TSDP and SDPC and obtained satisfying results with high convergence in reasonable time.
Gold thread implantation promotes hair growth in human and mice
Kim, Jong-Hwan; Cho, Eun-Young; Kwon, Euna; Kim, Woo-Ho; Park, Jin-Sung; Lee, Yong-Soon; Yun, Jun-Won; Kang, Byeong-Cheol
2017-01-01
Thread-embedding therapy has been widely applied for cosmetic purposes such as wrinkle reduction and skin tightening. Particularly, gold thread was reported to support connective tissue regeneration, but, its role in hair biology remains largely unknown due to lack of investigation. When we implanted gold thread and Happy Lift™ in human patient for facial lifting, we unexpectedly found an increase of hair regrowth in spite of no use of hair growth medications. When embedded into the depilated...
Protein Structure Prediction by Protein Threading
Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong
The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.
AN MHD AVALANCHE IN A MULTI-THREADED CORONAL LOOP
Energy Technology Data Exchange (ETDEWEB)
Hood, A. W.; Cargill, P. J.; Tam, K. V. [School of Mathematics and Statistics, University of St Andrews, St Andrews, Fife, KY16 9SS (United Kingdom); Browning, P. K., E-mail: awh@st-andrews.ac.uk [School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom)
2016-01-20
For the first time, we demonstrate how an MHD avalanche might occur in a multithreaded coronal loop. Considering 23 non-potential magnetic threads within a loop, we use 3D MHD simulations to show that only one thread needs to be unstable in order to start an avalanche even when the others are below marginal stability. This has significant implications for coronal heating in that it provides for energy dissipation with a trigger mechanism. The instability of the unstable thread follows the evolution determined in many earlier investigations. However, once one stable thread is disrupted, it coalesces with a neighboring thread and this process disrupts other nearby threads. Coalescence with these disrupted threads then occurs leading to the disruption of yet more threads as the avalanche develops. Magnetic energy is released in discrete bursts as the surrounding stable threads are disrupted. The volume integrated heating, as a function of time, shows short spikes suggesting that the temporal form of the heating is more like that of nanoflares than of constant heating.
Combinatorial optimization algorithms and complexity
Papadimitriou, Christos H
1998-01-01
This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. All chapters are supplemented by thought-provoking problems. A useful work for graduate-level students with backgrounds in computer science, operations research, and electrical engineering.
How the twain can meet: Prospect theory and models of heuristics in risky choice.
Pachur, Thorsten; Suter, Renata S; Hertwig, Ralph
2017-03-01
Two influential approaches to modeling choice between risky options are algebraic models (which focus on predicting the overt decisions) and models of heuristics (which are also concerned with capturing the underlying cognitive process). Because they rest on fundamentally different assumptions and algorithms, the two approaches are usually treated as antithetical, or even incommensurable. Drawing on cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as the currently most influential instance of a descriptive algebraic model, we demonstrate how the two modeling traditions can be linked. CPT's algebraic functions characterize choices in terms of psychophysical (diminishing sensitivity to probabilities and outcomes) as well as psychological (risk aversion and loss aversion) constructs. Models of heuristics characterize choices as rooted in simple information-processing principles such as lexicographic and limited search. In computer simulations, we estimated CPT's parameters for choices produced by various heuristics. The resulting CPT parameter profiles portray each of the choice-generating heuristics in psychologically meaningful ways-capturing, for instance, differences in how the heuristics process probability information. Furthermore, CPT parameters can reflect a key property of many heuristics, lexicographic search, and track the environment-dependent behavior of heuristics. Finally, we show, both in an empirical and a model recovery study, how CPT parameter profiles can be used to detect the operation of heuristics. We also address the limits of CPT's ability to capture choices produced by heuristics. Our results highlight an untapped potential of CPT as a measurement tool to characterize the information processing underlying risky choice. Copyright © 2017 Elsevier Inc. All rights reserved.
Heuristic Approach for Balancing Shift Schedules
International Nuclear Information System (INIS)
Kim, Dae Ho; Yun, Young Su; Lee, Yong Hee
2005-01-01
In this paper, a heuristic approach for balancing shift schedules is proposed. For the shift schedules, various constraints which have usually been considered in realworld industry are used, and the objective is to minimize the differences of the workloads in each workgroup. The constraints and objective function are implemented in the proposed heuristic approach. Using a simple instance, the efficiency of the proposed heuristic approach is proved
A single cognitive heuristic process meets the complexity of domain-specific moral heuristics.
Dubljević, Veljko; Racine, Eric
2014-10-01
The inherence heuristic (a) offers modest insights into the complex nature of both the is-ought tension in moral reasoning and moral reasoning per se, and (b) does not reflect the complexity of domain-specific moral heuristics. Formal and general in nature, we contextualize the process described as "inherence heuristic" in a web of domain-specific heuristics (e.g., agent specific; action specific; consequences specific).
Evaluating the multi-threading countermeasure
CSIR Research Space (South Africa)
Frieslaar, Ibraheem
2016-12-01
Full Text Available to obfuscate the individuals information from people attempting to intercept data. One of these cryptographic algorithms is the AES algorithm [1]. This algorithm has been declared to be the standard protocol to encrypt information by the The National Institute...-128 algo- rithm, four steps were followed: While the AES-128 algorithm was executing the encryption process, the power traces along with its corresponding input text were captured; a power leakage model was implemented where the guess of a key byte...
Algorithms in combinatorial design theory
Colbourn, CJ
1985-01-01
The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.
Algorithms for Decision Tree Construction
Chikalov, Igor
2011-01-01
The study of algorithms for decision tree construction was initiated in 1960s. The first algorithms are based on the separation heuristic [13, 31] that at each step tries dividing the set of objects as evenly as possible. Later Garey and Graham [28
Improving performances of suboptimal greedy iterative biclustering heuristics via localization.
Erten, Cesim; Sözdinler, Melih
2010-10-15
Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance
Meditope-Fab interaction: threading the hole.
Bzymek, Krzysztof P; Ma, Yuelong; Avery, Kendra N; Horne, David A; Williams, John C
2017-12-01
Meditope, a cyclic 12-residue peptide, binds to a unique binding side between the light and heavy chains of the cetuximab Fab. In an effort to improve the affinity of the interaction, it was sought to extend the side chain of Arg8 in the meditope, a residue that is accessible from the other side of the meditope binding site, in order to increase the number of interactions. These modifications included an n-butyl and n-octyl extension as well as hydroxyl, amine and carboxyl substitutions. The atomic structures of the complexes and the binding kinetics for each modified meditope indicated that each extension threaded through the Fab `hole' and that the carboxyethylarginine substitution makes a favorable interaction with the Fab, increasing the half-life of the complex by threefold compared with the unmodified meditope. Taken together, these studies provide a basis for the design of additional modifications to enhance the overall affinity of this unique interaction.
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Conspicuous Waste and Representativeness Heuristic
Directory of Open Access Journals (Sweden)
Tatiana M. Shishkina
2017-12-01
Full Text Available The article deals with the similarities between conspicuous waste and representativeness heuristic. The conspicuous waste is analyzed according to the classic Veblen’ interpretation as a strategy to increase social status through conspicuous consumption and conspicuous leisure. In “The Theory of the Leisure Class” Veblen introduced two different types of utility – conspicuous and functional. The article focuses on the possible benefits of the analysis of conspicuous utility not only in terms of institutional economic theory, but also in terms of behavioral economics. To this end, the representativeness heuristics is considered, on the one hand, as a way to optimize the decision-making process, which allows to examine it in comparison with procedural rationality by Simon. On the other hand, it is also analyzed as cognitive bias within the Kahneman and Twersky’ approach. The article provides the analysis of the patterns in the deviations from the rational behavior strategy that could be observed in case of conspicuous waste both in modern market economies in the form of conspicuous consumption and in archaic economies in the form of gift-exchange. The article also focuses on the marketing strategies for luxury consumption’ advertisement. It highlights the impact of the symbolic capital (in Bourdieu’ interpretation on the social and symbolic payments that actors get from the act of conspicuous waste. This allows to perform a analysis of conspicuous consumption both as a rational way to get the particular kind of payments, and, at the same time, as a form of institutionalized cognitive bias.
Integrating soft sensor systems using conductive thread
Teng, Lijun; Jeronimo, Karina; Wei, Tianqi; Nemitz, Markus P.; Lyu, Geng; Stokes, Adam A.
2018-05-01
We are part of a growing community of researchers who are developing a new class of soft machines. By using mechanically soft materials (MPa modulus) we can design systems which overcome the bulk-mechanical mismatches between soft biological systems and hard engineered components. To develop fully integrated soft machines—which include power, communications, and control sub-systems—the research community requires methods for interconnecting between soft and hard electronics. Sensors based upon eutectic gallium alloys in microfluidic channels can be used to measure normal and strain forces, but integrating these sensors into systems of heterogeneous Young’s modulus is difficult due the complexity of finding a material which is electrically conductive, mechanically flexible, and stable over prolonged periods of time. Many existing gallium-based liquid alloy sensors are not mechanically or electrically robust, and have poor stability over time. We present the design and fabrication of a high-resolution pressure-sensor soft system that can transduce normal force into a digital output. In this soft system, which is built on a monolithic silicone substrate, a galinstan-based microfluidic pressure sensor is integrated with a flexible printed circuit board. We used conductive thread as the interconnect and found that this method alleviates problems arising due to the mechanical mismatch between conventional metal wires and soft or liquid materials. Conductive thread is low-cost, it is readily wetted by the liquid metal, it produces little bending moment into the microfluidic channel, and it can be connected directly onto the copper bond-pads of the flexible printed circuit board. We built a bridge-system to provide stable readings from the galinstan pressure sensor. This system gives linear measurement results between 500-3500 Pa of applied pressure. We anticipate that integrated systems of this type will find utility in soft-robotic systems as used for wearable
A multi-threading approach to secure VERIFYPIN
CSIR Research Space (South Africa)
Frieslaar, Ibraheem
2016-10-01
Full Text Available along side a pin-acceptance program in a multi-threaded environment. These threads are inserted randomly on each execution of the program to create confusion for the attacker. Moreover, the research proposes a more improved version of the pin...
Dynamic thread assignment in web server performance optimization
van der Weij, W.; Bhulai, S.; van der Mei, R.D.
2009-01-01
Popular web sites are expected to handle huge number of requests concurrently within a reasonable time frame. The performance of these web sites is largely dependent on effective thread management of their web servers. Although the implementation of static and dynamic thread policies is common
Gold thread implantation promotes hair growth in human and mice
Kim, Jong-Hwan; Cho, Eun-Young; Kwon, Euna; Kim, Woo-Ho; Park, Jin-Sung; Lee, Yong-Soon
2017-01-01
Thread-embedding therapy has been widely applied for cosmetic purposes such as wrinkle reduction and skin tightening. Particularly, gold thread was reported to support connective tissue regeneration, but, its role in hair biology remains largely unknown due to lack of investigation. When we implanted gold thread and Happy Lift™ in human patient for facial lifting, we unexpectedly found an increase of hair regrowth in spite of no use of hair growth medications. When embedded into the depilated dorsal skin of mice, gold thread or polyglycolic acid (PGA) thread, similarly to 5% minoxidil, significantly increased the number of hair follicles on day 14 after implantation. And, hair re-growth promotion in the gold threadimplanted mice were significantly higher than that in PGA thread group on day 11 after depilation. In particular, the skin tissue of gold thread-implanted mice showed stronger PCNA staining and higher collagen density compared with control mice. These results indicate that gold thread implantation can be an effective way to promote hair re-growth although further confirmatory study is needed for more information on therapeutic mechanisms and long-term safety. PMID:29399026
The Probability Heuristics Model of Syllogistic Reasoning.
Chater, Nick; Oaksford, Mike
1999-01-01
Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…
Modeling reproductive decisions with simple heuristics
Directory of Open Access Journals (Sweden)
Peter Todd
2013-10-01
Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.
Cooperative heuristic multi-agent planning
De Weerdt, M.M.; Tonino, J.F.M.; Witteveen, C.
2001-01-01
In this paper we will use the framework to study cooperative heuristic multi-agent planning. During the construction of their plans, the agents use a heuristic function inspired by the FF planner (l3l). At any time in the process of planning the agents may exchange available resources, or they may
"A Heuristic for Visual Thinking in History"
Staley, David J.
2007-01-01
This article details a heuristic history teachers can use in assigning and evaluating multimedia projects in history. To use this heuristic successfully, requires more than simply following the steps in the list or stages in a recipe: in many ways, it requires a reorientation in what it means to think like an historian. This article, as much as…
Effective Heuristics for New Venture Formation
Kraaijenbrink, Jeroen
2010-01-01
Entrepreneurs are often under time pressure and may only have a short window of opportunity to launch their new venture. This means they often have no time for rational analytical decisions and rather rely on heuristics. Past research on entrepreneurial heuristics has primarily focused on predictive
Religion, Heuristics, and Intergenerational Risk Management
Rupert Read; Nassim Nicholas Taleb
2014-01-01
Religions come with risk-managing interdicts and heuristics, and they carry such interdicts and heuristics across generations. We remark on such facets of religion in relation to a propensity among some decision scientists and others to regard practices that they cannot understand as being irrational, biased, and so on.
Heuristic Optimization for the Discrete Virtual Power Plant Dispatch Problem
DEFF Research Database (Denmark)
Petersen, Mette Kirschmeyer; Hansen, Lars Henrik; Bendtsen, Jan Dimon
2014-01-01
We consider a Virtual Power Plant, which is given the task of dispatching a fluctuating power supply to a portfolio of flexible consumers. The flexible consumers are modeled as discrete batch processes, and the associated optimization problem is denoted the Discrete Virtual Power Plant Dispatch...... Problem. First NP-completeness of the Discrete Virtual Power Plant Dispatch Problem is proved formally. We then proceed to develop tailored versions of the meta-heuristic algorithms Hill Climber and Greedy Randomized Adaptive Search Procedure (GRASP). The algorithms are tuned and tested on portfolios...... of varying sizes. We find that all the tailored algorithms perform satisfactorily in the sense that they are able to find sub-optimal, but usable, solutions to very large problems (on the order of 10 5 units) at computation times on the scale of just 10 seconds, which is far beyond the capabilities...
Tuning Parameters in Heuristics by Using Design of Experiments Methods
Arin, Arif; Rabadi, Ghaith; Unal, Resit
2010-01-01
With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.
Matlab enhanced multi-threaded tomography optimization sequence (MEMTOS)
International Nuclear Information System (INIS)
Lum, Edward S.; Pope, Chad L.
2016-01-01
Highlights: • Monte Carlo simulation of spent nuclear fuel assembly neutron computed tomography. • Optimized parallel calculations conducted from within the MATLAB environment. • Projection difference technique used to identify anomalies in spent nuclear fuel assemblies. - Abstract: One challenge associated with spent nuclear fuel assemblies is the lack of non-destructive analysis techniques to determine if fuel pins have been removed or replaced or if there are significant defects associated with fuel pins deep within a fuel assembly. Neutron computed tomography is a promising technique for addressing these qualitative issues. Monte Carlo simulation of spent nuclear fuel neutron computed tomography allows inexpensive process investigation and optimization. The main purpose of this work is to provide a fully automated advanced simulation framework for the analysis of spent nuclear fuel inspection using neutron computed tomography. The simulation framework, called Matlab Enhanced Multi-Threaded Tomography Optimization Sequence (MEMTOS) not only automates the simulation process, but also generates superior tomography image results. MEMTOS is written in the MATLAB scripting language and addresses file management, parallel Monte Carlo execution, results extraction, and tomography image generation. This paper describes the mathematical basis for neutron computed tomography, the Monte Carlo technique used to simulate neutron computed tomography, and the overall tomography simulation optimization algorithm. Sequence results presented include overall simulation speed enhancement, tomography and image results obtained for Experimental Breeder Reactor II spent fuel assemblies and light water reactor fuel assemblies. Optimization using a projection difference technique are also described.
Heuristics Miner for E-Commerce Visitor Access Pattern Representation
Directory of Open Access Journals (Sweden)
Kartina Diah Kesuma Wardhani
2017-06-01
Full Text Available E-commerce click stream data can form a certain pattern that describe visitor behavior while surfing the e-commerce website. This pattern can be used to initiate a design to determine alternative access sequence on the website. This research use heuristic miner algorithm to determine the pattern. σ-Algorithm and Genetic Mining are methods used for pattern recognition with frequent sequence item set approach. Heuristic Miner is an evolved form of those methods. σ-Algorithm assume that an activity in a website, that has been recorded in the data log, is a complete sequence from start to finish, without any tolerance to incomplete data or data with noise. On the other hand, Genetic Mining is a method that tolerate incomplete data or data with noise, so it can generate a more detailed e-commerce visitor access pattern. In this study, the same sequence of events obtained from six-generated patterns. The resulting pattern of visitor access is that visitors are often access the home page and then the product category page or the home page and then the full text search page.
Directory of Open Access Journals (Sweden)
G. Esteve-Asensio
2009-01-01
Full Text Available We propose and compare three novel heuristics for the calculation of the optimal cell radius in mobile networks based on Wideband Code Division Multiple Access (WCDMA technology. The proposed heuristics solve the problem of the load assignment and cellular radius calculation. We have tested our approaches with experiments in multiservices scenarios showing that the proposed heuristics maximize the cell radius, providing the optimum load factor assignment. The main application of these algorithms is strategic planning studies, where an estimation of the number of Nodes B of the mobile operator, at a national level, is required for economic analysis. In this case due to the large number of different scenarios considered (cities, towns, and open areas other methods than simulation need to be considered. As far as we know, there is no other similar method in the literature and therefore these heuristics may represent a novelty in strategic network planning studies. The proposed heuristics are implemented in a strategic planning software tool and an example of their application for a case in Spain is presented. The proposed heuristics are used for telecommunications regulatory studies in several countries.
Heuristics for multiobjective multiple sequence alignment.
Abbasi, Maryam; Paquete, Luís; Pereira, Francisco B
2016-07-15
Aligning multiple sequences arises in many tasks in Bioinformatics. However, the alignments produced by the current software packages are highly dependent on the parameters setting, such as the relative importance of opening gaps with respect to the increase of similarity. Choosing only one parameter setting may provide an undesirable bias in further steps of the analysis and give too simplistic interpretations. In this work, we reformulate multiple sequence alignment from a multiobjective point of view. The goal is to generate several sequence alignments that represent a trade-off between maximizing the substitution score and minimizing the number of indels/gaps in the sum-of-pairs score function. This trade-off gives to the practitioner further information about the similarity of the sequences, from which she could analyse and choose the most plausible alignment. We introduce several heuristic approaches, based on local search procedures, that compute a set of sequence alignments, which are representative of the trade-off between the two objectives (substitution score and indels). Several algorithm design options are discussed and analysed, with particular emphasis on the influence of the starting alignment and neighborhood search definitions on the overall performance. A perturbation technique is proposed to improve the local search, which provides a wide range of high-quality alignments. The proposed approach is tested experimentally on a wide range of instances. We performed several experiments with sequences obtained from the benchmark database BAliBASE 3.0. To evaluate the quality of the results, we calculate the hypervolume indicator of the set of score vectors returned by the algorithms. The results obtained allow us to identify reasonably good choices of parameters for our approach. Further, we compared our method in terms of correctly aligned pairs ratio and columns correctly aligned ratio with respect to reference alignments. Experimental results show
Multiobjective hyper heuristic scheme for system design and optimization
Rafique, Amer Farhan
2012-11-01
As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.
Improving the Bin Packing Heuristic through Grammatical Evolution Based on Swarm Intelligence
Directory of Open Access Journals (Sweden)
Marco Aurelio Sotelo-Figueroa
2014-01-01
Full Text Available In recent years Grammatical Evolution (GE has been used as a representation of Genetic Programming (GP which has been applied to many optimization problems such as symbolic regression, classification, Boolean functions, constructed problems, and algorithmic problems. GE can use a diversity of searching strategies including Swarm Intelligence (SI. Particle Swarm Optimisation (PSO is an algorithm of SI that has two main problems: premature convergence and poor diversity. Particle Evolutionary Swarm Optimization (PESO is a recent and novel algorithm which is also part of SI. PESO uses two perturbations to avoid PSO’s problems. In this paper we propose using PESO and PSO in the frame of GE as strategies to generate heuristics that solve the Bin Packing Problem (BPP; it is possible however to apply this methodology to other kinds of problems using another Grammar designed for that problem. A comparison between PESO, PSO, and BPP’s heuristics is performed through the nonparametric Friedman test. The main contribution of this paper is proposing a Grammar to generate online and offline heuristics depending on the test instance trying to improve the heuristics generated by other grammars and humans; it also proposes a way to implement different algorithms as search strategies in GE like PESO to obtain better results than those obtained by PSO.
Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account
Renkl, Alexander; Hilbert, Tatjana; Schworm, Silke
2009-01-01
One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies…
Heuristic Strategies in Systems Biology
Directory of Open Access Journals (Sweden)
Fridolin Gross
2016-06-01
Full Text Available Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences.
THE HEURISTIC FUNCTION OF SPORT
Directory of Open Access Journals (Sweden)
Adam Petrović
2012-09-01
Full Text Available Being a significant area of human activity, sport has multiple functions. One of the more important functions of sport, especially top sport, is the inventive heuristic function. Creative work, being a process of creating new values, represents a significant possibility for advancement of sport. This paper aims at pointing at the various dimensions of human creative work, at the creative work which can be seen in sport (in a narrow sense and at the scientific and practical areas which borderline sport. The method of theoretical analysis of different approaches to the phenomenon of creative work , both in general and in sport, was applied in this paper. This area can be systematized according to various criterion : the level of creative work, different fields where it appears, the subjects of creative work - creators etc. Case analysis shows that the field of creative work in sport is widening and deepening constantly. There are different levels of creativity not only in the system of training and competition, but in a wider social context of sport as well. As a process of human spirit and mind the creative work belongs not just to athletes and coaches, but also to all the people and social groups who's creative power manifests itself in sport. The classification of creative work in sport according to various criterion allows for heuristic function of sport to be explained comprehensively and to create an image how do the sparks of human spirit improve the micro cosmos of sport. A thorough classification of creative work in sport allows for a detailed analysis of all the elements of creative work and each of it’s area in sport. In this way the progress in sport , as a consequence of innovations in both competitions and athletes’ training and of everything that goes with those activities, can be guided into the needed direction more easily as well as studied and applied.
Carbon Nanotube Thread Electrochemical Cell: Detection of Heavy Metals.
Zhao, Daoli; Siebold, David; Alvarez, Noe T; Shanov, Vesselin N; Heineman, William R
2017-09-19
In this work, all three electrodes in an electrochemical cell were fabricated based on carbon nanotube (CNT) thread. CNT thread partially insulated with a thin polystyrene coating to define the microelectrode area was used as the working electrode; bare CNT thread was used as the auxiliary electrode; and a micro quasi-reference electrode was fabricated by electroplating CNT thread with Ag and then anodizing it in chloride solution to form a layer of AgCl. The Ag|AgCl coated CNT thread electrode provided a stable potential comparable to the conventional liquid-junction type Ag|AgCl reference electrode. The CNT thread auxiliary electrode provided a stable current, which is comparable to a Pt wire auxiliary electrode. This all-CNT thread three electrode cell has been evaluated as a microsensor for the simultaneous determination of trace levels of heavy metal ions by anodic stripping voltammetry (ASV). Hg 2+ , Cu 2+ , and Pb 2+ were used as a representative system for this study. The calculated detection limits (based on the 3σ method) with a 120 s deposition time are 1.05, 0.53, and 0.57 nM for Hg 2+ , Cu 2+ , and Pb 2+ , respectively. These electrodes significantly reduce the dimensions of the conventional three electrode electrochemical cell to the microscale.
A Moiré Pattern-Based Thread Counter
Reich, Gary
2017-10-01
Thread count is a term used in the textile industry as a measure of how closely woven a fabric is. It is usually defined as the sum of the number of warp threads per inch (or cm) and the number of weft threads per inch. (It is sometimes confusingly described as the number of threads per square inch.) In recent years it has also become a subject of considerable interest and some controversy among consumers. Many consumers consider thread count to be a key measure of the quality or fineness of a fabric, especially bed sheets, and they seek out fabrics that advertise high counts. Manufacturers in turn have responded to this interest by offering fabrics with ever higher claimed thread counts (sold at ever higher prices), sometime achieving the higher counts by distorting the definition of the term with some "creative math." In 2005 the Federal Trade Commission noted the growing use of thread count in advertising at the retail level and warned of the potential for consumers to be misled by distortions of the definition.
Outcomes of polydioxanone knotless thread lifting for facial rejuvenation.
Suh, Dong Hye; Jang, Hee Won; Lee, Sang Jun; Lee, Won Seok; Ryu, Hwa Jung
2015-06-01
Thread lifting is a minimally invasive technique for facial rejuvenation. Various devices for thread lifting using polydioxanone (PDO) are popular in aesthetic clinics in Korea, but there have been a few studies regarding its use. To describe PDO thread and techniques adopted to counteract the descent and laxity of the face. A retrospective chart review was conducted over a 24-month period. A total of 31 thread lifting procedures were performed. On each side, 5 bidirectional cog threads were used in the procedure for the flabby skin of the nasolabial folds. And, the procedure was performed on the marionette line using 2 twin threads. In most patients (87%), the results obtained were considered satisfactory. Consensus ratings by 2 physicians found that objective outcomes were divided among "excellent," "good," "fair," and "poor." Texture wise, the outcome ratings were 13 as excellent and 9 as good. Lifting wise, ratings were 11 as excellent and 6 as good. The incidence of complications was low and not serious. Facial rejuvenation using PDO thread is a safe and effective procedure associated with only minor complications when performed on patients with modest face sagging, fine wrinkles, and marked facial pores.
Radiometric determination of uniformity of putting paraffin on textile threads
International Nuclear Information System (INIS)
Ridel', Z.; Kherrmann, Eh.; Shefer, I.; Tseiner, A.
1979-01-01
To improve processing of the natural and synthetic fiber threads on stocking-frames, they are treated by paraffin. Paraffin is applied in the amounts nearly equal to 0.1 -1.0 g for 10 4 m of the thread's length. To determine amount of paraffin on thread and to determine uniformity if its application, a radiometric method has been developed. As a radioactive label, didocilephosphate of rare earths was used. This compound has good solubility in hydrocarbons and does not change physical properties of paraffin in the investigated field of its application as well as its concentration. It is possible to add to paraffin this radioactive label or a non-active label with subsequent its activation. Amount of paraffin, applied on a thread is determined by means of measurement of activity of thread samples of different length. Information about uniformity of paraffin application on thread have been obtained by means of autoradiography. It has been found that paraffin in mainly applied on the thread's bulges [ru
Ryan, Jason C; Banerjee, Ashis Gopal; Cummings, Mary L; Roy, Nicholas
2014-06-01
Planning operations across a number of domains can be considered as resource allocation problems with timing constraints. An unexplored instance of such a problem domain is the aircraft carrier flight deck, where, in current operations, replanning is done without the aid of any computerized decision support. Rather, veteran operators employ a set of experience-based heuristics to quickly generate new operating schedules. These expert user heuristics are neither codified nor evaluated by the United States Navy; they have grown solely from the convergent experiences of supervisory staff. As unmanned aerial vehicles (UAVs) are introduced in the aircraft carrier domain, these heuristics may require alterations due to differing capabilities. The inclusion of UAVs also allows for new opportunities for on-line planning and control, providing an alternative to the current heuristic-based replanning methodology. To investigate these issues formally, we have developed a decision support system for flight deck operations that utilizes a conventional integer linear program-based planning algorithm. In this system, a human operator sets both the goals and constraints for the algorithm, which then returns a proposed schedule for operator approval. As a part of validating this system, the performance of this collaborative human-automation planner was compared with that of the expert user heuristics over a set of test scenarios. The resulting analysis shows that human heuristics often outperform the plans produced by an optimization algorithm, but are also often more conservative.
Automatic Generation of Heuristics for Scheduling
Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.
1997-01-01
This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
Exploiting Thread Parallelism for Ocean Modeling on Cray XC Supercomputers
Energy Technology Data Exchange (ETDEWEB)
Sarje, Abhinav [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jacobsen, Douglas W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Samuel W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ringler, Todd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2016-05-01
The incorporation of increasing core counts in modern processors used to build state-of-the-art supercomputers is driving application development towards exploitation of thread parallelism, in addition to distributed memory parallelism, with the goal of delivering efficient high-performance codes. In this work we describe the exploitation of threading and our experiences with it with respect to a real-world ocean modeling application code, MPAS-Ocean. We present detailed performance analysis and comparisons of various approaches and configurations for threading on the Cray XC series supercomputers.
Z-2 Threaded Insert Design and Testing
Ross, Amy; Rhodes, Richard; Jones, Robert J.; Graziosi, David; Ferl, Jinny; Sweeny, Mitch; Scarborough, Stephen
2016-01-01
NASA's Z-2 prototype space suit contains several components fabricated from an advanced hybrid composite laminate consisting of IM10 carbon fiber and fiber glass. One requirement was to have removable, replaceable helicoil inserts to which other suit components would be fastened. An approach utilizing bonded in inserts with helicoils inside of them was implemented. During initial assembly, cracking sounds were heard followed by the lifting of one of the blind inserts out of its hole when the screws were torqued. A failure investigation was initiated to understand the mechanism of the failure. Ultimately, it was determined that the pre-tension caused by torqueing the fasteners is a much larger force than induced from the pressure loads of the suit which was not considered in the insert design. Bolt tension is determined by dividing the torque on the screw by a k value multiplied by the thread diameter of the bolt. The k value is a factor that accounts for friction in the system. A common value used for k for a non-lubricated screw is 0.2. The k value can go down by as much as 0.1 if the screw is lubricated which means for the same torque, a much larger tension could be placed on the bolt and insert. This paper summarizes the failure investigation that was performed to identify the root cause of the suit failure and details how the insert design was modified to resist a higher pull out tension.
A novel heuristic method for optimization of straight blade vertical axis wind turbine
International Nuclear Information System (INIS)
Tahani, Mojtaba; Babayan, Narek; Mehrnia, Seyedmajid; Shadmehri, Mehran
2016-01-01
Highlights: • A novel heuristic method has been proposed for optimization of VAWTs. • The proposed method is the combination of DMST model with heuristic algorithms. • A continuous/discrete optimization problem has been solved. • A novel continuous optimization algorithm has been developed. • The CFD simulation of the optimized geometry has been carried out. - Abstract: In this research study it is aimed to propose a novel heuristic method for optimizing the VAWT design. The method is the combination of continuous/discrete optimization algorithms with double multiple stream tube (DMST) theory. For this purpose a DMST code has been developed and is validated using available experimental data in literature. A novel continuous optimization algorithm is proposed which can be considered as the combination of three heuristic optimization algorithms namely elephant herding optimization, flower pollination algorithm and grey wolf optimizer. The continuous algorithm is combined with popular discrete ant colony optimization algorithm (ACO). The proposed method can be utilized for several engineering problems which are dealing with continuous and discrete variables. In this research study, chord and diameter of the turbine are selected as continuous decision variables and airfoil types and number of blades are selected as discrete decision variables. The average power coefficient between tip speed rations from 1.5 to 9.5 is considered as the objective function. The optimization results indicated that the optimized geometry can produce a maximum power coefficient, 44% higher than the maximum power coefficient of the original turbine. Also a CFD simulation of the optimized geometry is carried out. The CFD results indicated that the average vorticity magnitude around the optimized blade is larger than the original blade and this results greater momentum and power coefficient.
Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot
Marcin Szuster; Zenon Hendzel
2014-01-01
Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal...
A review of parameters and heuristics for guiding metabolic pathfinding.
Kim, Sarah M; Peña, Matthew I; Moll, Mark; Bennett, George N; Kavraki, Lydia E
2017-09-15
Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases. However, the recent rapid development of available metabolic information has enabled the development of automated approaches for identifying novel pathways. Computer-assisted pathfinding has the potential to save biochemists time in the initial discovery steps of metabolic engineering. In this paper, we review the parameters and heuristics used to guide the search in recent pathfinding algorithms. These parameters and heuristics capture information on the metabolic network structure, compound structures, reaction features, and organism-specificity of pathways. No one metabolic pathfinding algorithm or search parameter stands out as the best to use broadly for solving the pathfinding problem, as each method and parameter has its own strengths and shortcomings. As assisted pathfinding approaches continue to become more sophisticated, the development of better methods for visualizing pathway results and integrating these results into existing metabolic engineering practices is also important for encouraging wider use of these pathfinding methods.
A heuristic for efficient data distribution management in distributed simulation
Gupta, Pankaj; Guha, Ratan K.
2005-05-01
In this paper, we propose an algorithm for reducing the complexity of region matching and efficient multicasting in data distribution management component of High Level Architecture (HLA) Run Time Infrastructure (RTI). The current data distribution management (DDM) techniques rely on computing the intersection between the subscription and update regions. When a subscription region and an update region of different federates overlap, RTI establishes communication between the publisher and the subscriber. It subsequently routes the updates from the publisher to the subscriber. The proposed algorithm computes the update/subscription regions matching for dynamic allocation of multicast group. It provides new multicast routines that exploit the connectivity of federation by communicating updates regarding interactions and routes information only to those federates that require them. The region-matching problem in DDM reduces to clique-covering problem using the connections graph abstraction where the federations represent the vertices and the update/subscribe relations represent the edges. We develop an abstract model based on connection graph for data distribution management. Using this abstract model, we propose a heuristic for solving the region-matching problem of DDM. We also provide complexity analysis of the proposed heuristics.
A manpower scheduling heuristic for aircraft maintenance application
Sze, San-Nah; Sze, Jeeu-Fong; Chiew, Kang-Leng
2012-09-01
This research studies a manpower scheduling for aircraft maintenance, focusing on in-flight food loading operation. A group of loading teams with flexible shifts is required to deliver and upload packaged meals from the ground kitchen to aircrafts in multiple trips. All aircrafts must be served within predefined time windows. The scheduling process takes into account of various constraints such as meal break allocation, multi-trip traveling and food exposure time limit. Considering the aircrafts movement and predefined maximum working hours for each loading team, the main objective of this study is to form an efficient roster by assigning a minimum number of loading teams to the aircrafts. We proposed an insertion based heuristic to generate the solutions in a short period of time for large instances. This proposed algorithm is implemented in various stages for constructing trips due to the presence of numerous constraints. The robustness and efficiency of the algorithm is demonstrated in computational results. The results show that the insertion heuristic more efficiently outperforms the company's current practice.
Solving Inventory Routing Problems Using Location Based Heuristics
Directory of Open Access Journals (Sweden)
Paweł Hanczar
2014-01-01
Full Text Available Inventory routing problems (IRPs occur where vendor managed inventory replenishment strategies are implemented in supply chains. These problems are characterized by the presence of both transportation and inventory considerations, either as parameters or constraints. The research presented in this paper aims at extending IRP formulation developed on the basis of location based heuristics proposed by Bramel and Simchi-Levi and continued by Hanczar. In the first phase of proposed algorithms, mixed integer programming is used to determine the partitioning of customers as well as dates and quantities of deliveries. Then, using 2-opt algorithm for solving the traveling sales-person problem the optimal routes for each partition are determined. In the main part of research the classical formulation is extended by additional constraints (visit spacing, vehicle filling rate, driver (vehicle consistency, and heterogeneous fleet of vehicles as well as the additional criteria are discussed. Then the impact of using each of proposed extensions for solution possibilities is evaluated. The results of computational tests are presented and discussed. Obtained results allow to conclude that the location based heuristics should be considered when solving real life instances of IRP. (original abstract
The Effect of Incentive Structure on Heuristic Decision Making: The Proportion Heuristic
Robert Oxoby
2007-01-01
When making judgments, individuals often utilize heuristics to interpret information. We report on a series of experiments designed to test the ways in which incentive mechanisms influence the use of a particular heuristic in decision-making. Specifically, we demonstrate how information regarding the number of available practice problems influences the behaviors of individuals preparing for an exam (the proportion heuristic). More importantly the extent to which this information influences be...
P-Refinement and P-Threads (Preprint)
National Research Council Canada - National Science Library
Dong, Steven; Karniadakis, George E
2002-01-01
...]) in d dimensions, which is higher than lower-order methods. In this paper, we demonstrate that by employing multi-threading within MPI processes we manage to counter- balance the cost increase associated with P-refinement...
Threaded cognition: an integrated theory of concurrent multitasking.
Salvucci, Dario D; Taatgen, Niels A
2008-01-01
The authors propose the idea of threaded cognition, an integrated theory of concurrent multitasking--that is, performing 2 or more tasks at once. Threaded cognition posits that streams of thought can be represented as threads of processing coordinated by a serial procedural resource and executed across other available resources (e.g., perceptual and motor resources). The theory specifies a parsimonious mechanism that allows for concurrent execution, resource acquisition, and resolution of resource conflicts, without the need for specialized executive processes. By instantiating this mechanism as a computational model, threaded cognition provides explicit predictions of how multitasking behavior can result in interference, or lack thereof, for a given set of tasks. The authors illustrate the theory in model simulations of several representative domains ranging from simple laboratory tasks such as dual-choice tasks to complex real-world domains such as driving and driver distraction. (c) 2008 APA, all rights reserved
Heuristic attacks against graphical password generators
CSIR Research Space (South Africa)
Peach, S
2010-05-01
Full Text Available In this paper the authors explore heuristic attacks against graphical password generators. A new trend is emerging to use user clickable pictures to generate passwords. This technique of authentication can be successfully used for - for example...
Hermawati, Setia; Lawson, Glyn
2016-09-01
Heuristics evaluation is frequently employed to evaluate usability. While general heuristics are suitable to evaluate most user interfaces, there is still a need to establish heuristics for specific domains to ensure that their specific usability issues are identified. This paper presents a comprehensive review of 70 studies related to usability heuristics for specific domains. The aim of this paper is to review the processes that were applied to establish heuristics in specific domains and identify gaps in order to provide recommendations for future research and area of improvements. The most urgent issue found is the deficiency of validation effort following heuristics proposition and the lack of robustness and rigour of validation method adopted. Whether domain specific heuristics perform better or worse than general ones is inconclusive due to lack of validation quality and clarity on how to assess the effectiveness of heuristics for specific domains. The lack of validation quality also affects effort in improving existing heuristics for specific domain as their weaknesses are not addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Hybrid Approach for Thread Recommendation in MOOC Forums
Ahmad. A. Kardan; Amir Narimani; Foozhan Ataiefard
2017-01-01
Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC ...
Threaded-fastener experience in nuclear power plants
International Nuclear Information System (INIS)
Koo, W.H.
1983-01-01
This report identifies 44 incidents of threaded-fastener degradation and failure in nuclear power plants from October 1964 to March 1982. It provides an overview of some of the threaded-fastener problems that have occurred since 1964. Safety implications of these incidents are discussed, and short-term regulatory actions and ongoing long-term regulatory actions are described. Information included in this report represents the current NRC staff understanding of each issue
Nuclear reactor incorporating locking device for threaded bolt connections
International Nuclear Information System (INIS)
Blaushild, R.M.
1987-01-01
A nuclear reactor having a pressure vessel and a first element is described comprising a core barrel situated within the pressure vessel. The core barrel has a baffle former secured in and to the core barrel by bolted connections, and a second element comprising baffle plates secured to the inner surface of the baffle former by bolted connections, with a locking device to prevent loosening of bolted connections between the baffle former and at least one of the elements. The baffle former and at least one element are held together by a headed, threaded bolt engaged in a bore coaxially extending in the baffle former and at least one element and threadedly engaged in a threaded section in at least the baffle former. The threaded section has first threaded of a first direction, with the head of the bolt engaged with a shoulder about the bore in at least one element to hold the baffle formed and at least one element together, the head of the bolt having a first diameter and a cavity, having an unsymmetrical wall thereabout, in the end surface thereof. It comprises a recess in at least one element coaxial with the bore forming a wall thereabout and extending inwardly from the outer surface of at least one element, the recess having a second diameter greater than the first diameter, with at least one element having second threads in the wall of a direction opposite the direction of the first threads of the threaded bore; a locking nut having a base with a downwardly depending cylindrical wall thereabout
A heuristic forecasting model for stock decision
Zhang, D.; Jiang, Q.; Li, X.
2005-01-01
This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...
Psychology into economics: fast and frugal heuristics
Schilirò, Daniele
2015-01-01
The present essay focuses on the fast and frugal heuristics program set forth by Gerd Gigerenzer and his fellows. In particular it examines the contribution of Gigerenzer and Goldstein (1996) ‘Reasoning the Fast and Frugal Way: Models of Bounded Rationality’. This essay, following the theoretical propositions and the empirical evidence of Gigerenzer and Goldstein, points out that simple cognitive mechanisms such as fast and frugal heuristics can be capable of successful performance in real wo...
Arational heuristic model of economic decision making
Grandori, Anna
2010-01-01
The article discuss the limits of both the rational actor and the behavioral paradigms in explaining and guiding innovative decision making and outlines a model of economic decision making that in the course of being 'heuristic' (research and discovery oriented) is also 'rational' (in the broad sense of following correct reasoning and scientific methods, non 'biasing'). The model specifies a set of 'rational heuristics' for innovative decision making, for the various sub-processes of problem ...
Social heuristics shape intuitive cooperation.
Rand, David G; Peysakhovich, Alexander; Kraft-Todd, Gordon T; Newman, George E; Wurzbacher, Owen; Nowak, Martin A; Greene, Joshua D
2014-04-22
Cooperation is central to human societies. Yet relatively little is known about the cognitive underpinnings of cooperative decision making. Does cooperation require deliberate self-restraint? Or is spontaneous prosociality reined in by calculating self-interest? Here we present a theory of why (and for whom) intuition favors cooperation: cooperation is typically advantageous in everyday life, leading to the formation of generalized cooperative intuitions. Deliberation, by contrast, adjusts behaviour towards the optimum for a given situation. Thus, in one-shot anonymous interactions where selfishness is optimal, intuitive responses tend to be more cooperative than deliberative responses. We test this 'social heuristics hypothesis' by aggregating across every cooperation experiment using time pressure that we conducted over a 2-year period (15 studies and 6,910 decisions), as well as performing a novel time pressure experiment. Doing so demonstrates a positive average effect of time pressure on cooperation. We also find substantial variation in this effect, and show that this variation is partly explained by previous experience with one-shot lab experiments.
Fabrication and Characterisation of Flexible Coaxial Thin Thread Supercapacitors
Directory of Open Access Journals (Sweden)
Fulian Qiu
2014-08-01
Full Text Available Flexible coaxial thin thread supercapacitors were fabricated semi-automatically using a dip coating method. A typical coaxial thin thread supercapacitor of a length of 70 cm demonstrated a specific length capacitance of 0.3 mF cm-1 (11.2 mF cm-2 and 2.18 F cm-3 at 5 mV s-1, the device exhibited good electrochemical performance with a high volume energy density of 0.22 mWh cm-3 at a power density of 22 mW cm-3. Thread supercapacitors were assembled in series and parallel combinations, the accepted models for series and parallel circuit combinations were obeyed for two coaxial thread supercapacitors. The thread shows high flexibility and uniformity of specific length capacitance, one integrated with a commercial solar cell could be charged and power a LED. The process is simple, robust and easy to scale up to make unlimited length thread supercapacitors for numerous miniaturized and flexible electronic applications.
Redoable Tie-Over Dressing Using Multiple Loop Silk Threads
Directory of Open Access Journals (Sweden)
Hyeon Jong Jo
2013-05-01
Full Text Available After skin grafting, to prevent hematoma or seroma collection at the graft site, a tie-over dressing has been commonly used. However, although the conventional tie-over dressing by suture is a useful method for securing a graft site, refixation is difficult when repeated tie-over dressing is needed. Therefore, we recommend a redoable tie-over dressing technique with multiple loops threads and connecting silk threads. After the raw surface of each of our cases was covered with a skin graft, multiple loop silk thread attached with nylon at the skin graft margin. We applied the ointment gauze and wet cotton/fluffy gauze over the skin graft, then fixed the dressing by connecting cross-counter multiple loop thread with connecting silk threads. When we opened the tie-over dressing by cutting the connecting silk threads, we repeated the tie-over dressing with the same method. The skin graft was taken successfully without hematoma or seroma collection or any other complications. In conclusion, we report a novel tie-over dressing enabling simple fixation of the dressing to maintain proper tension for wounds that require repetitive fixation. Further, with this reliable method, the skin grafts were well taken.
Redoable Tie-Over Dressing Using Multiple Loop Silk Threads
Directory of Open Access Journals (Sweden)
Hyeon Jong Jo
2013-05-01
Full Text Available After skin grafting, to prevent hematoma or seroma collection at the graft site, a tie-over dressing has been commonly used. However, although the conventional tie-over dressing by suture is a useful method for securing a graft site, refixation is difficult when repeated tieover dressing is needed. Therefore, we recommend a redoable tie-over dressing technique with multiple loops threads and connecting silk threads. After the raw surface of each of our cases was covered with a skin graft, multiple loop silk thread attached with nylon at the skin graft margin. We applied the ointment gauze and wet cotton/fluffy gauze over the skin graft, then fixed the dressing by connecting cross-counter multiple loop thread with connecting silk threads. When we opened the tie-over dressing by cutting the connecting silk threads, we repeated the tie-over dressing with the same method. The skin graft was taken successfully without hematoma or seroma collection or any other complications. In conclusion, we report a novel tie-over dressing enabling simple fixation of the dressing to maintain proper tension for wounds that require repetitive fixation. Further, with this reliable method, the skin grafts were well taken.
Algorithms and ordering heuristics for distributed constraint satisfaction problems
Wahbi , Mohamed
2013-01-01
DisCSP (Distributed Constraint Satisfaction Problem) is a general framework for solving distributed problems arising in Distributed Artificial Intelligence.A wide variety of problems in artificial intelligence are solved using the constraint satisfaction problem paradigm. However, there are several applications in multi-agent coordination that are of a distributed nature. In this type of application, the knowledge about the problem, that is, variables and constraints, may be logically or geographically distributed among physical distributed agents. This distribution is mainly due to p
Heuristic algorithms for scheduling heat-treatment furnaces of steel ...
Indian Academy of Sciences (India)
1Department of Management Studies, Indian Institute of Science,. Bangalore .... and scheduling, production monitoring and data capture, and management information. Southall ...... Project Report, Department of Management Studies, Indian.
Two phase heuristic algorithm for the university course timetabling
African Journals Online (AJOL)
Mgina
Department of Mathematics, Box 35062, University of Dar es salaam, Tanzania ... and rooms to a number of timeslots over a planning horizon, normally a week, while ... Solutions have been generated which greatly outperform the manually ...
Instructional Regulation and Control: Cybernetics, Algorithmization and Heuristics in Education.
Landa, L. N.; And Others
This book on the aspects of instructional processes focuses on control of student cognitive activity during instruction. Chapter 1 introduces the cybernetic approach to the theory of instruction. It is followed by a chapter on instructional effectiveness and efficiency. The third chapter discusses cognitive processes and thinking. Chapter 4…
A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters
Weiwei Lin; Wentai Wu; James Z. Wang
2016-01-01
Cloud computing provides on-demand computing and storage services with high performance and high scalability. However, the rising energy consumption of cloud data centers has become a prominent problem. In this paper, we first introduce an energy-aware framework for task scheduling in virtual clusters. The framework consists of a task resource requirements prediction module, an energy estimate module, and a scheduler with a task buffer. Secondly, based on this framework, we propose a virtual ...
Yang, S; Wang, D
2000-01-01
This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.
Simple heuristics and rules of thumb: where psychologists and behavioural biologists might meet.
Hutchinson, John M C; Gigerenzer, Gerd
2005-05-31
The Centre for Adaptive Behaviour and Cognition (ABC) has hypothesised that much human decision-making can be described by simple algorithmic process models (heuristics). This paper explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of Take The Best for choosing between two alternatives: cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modelling is usually used to explain less detailed aspects of behaviour but might more often be redirected to investigate rules of thumb.
Directory of Open Access Journals (Sweden)
Qi Xu
2016-01-01
Full Text Available This paper proposes an economic production quantity problem with the maximal production run time and minimal preventive maintenance time over a finite planning horizon. The objective is to find the efficient production and maintenance policy to minimize the total cost composed of production, maintenance, shortages, and holding costs under the restriction on the production run time and the preventive maintenance time. The production and maintenance decisions include the production and maintenance frequencies and the production run and the maintenance time. The variability and the boundedness of the production run and maintenance time make the problem difficult to solve. Two heuristic algorithms are developed using different techniques based on the optimal properties of the relaxed problem. The performance comparison between the two algorithms is illustrated by numerical examples. The numerical results show that, for the most part, there exists a heuristic algorithm which is more effective than the other.
An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics
Baluja, Shumeet
1995-01-01
This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.
Azad, Mohammad; Moshkov, Mikhail
2014-01-01
A greedy algorithm has been presented in this paper to construct decision trees for three different approaches (many-valued decision, most common decision, and generalized decision) in order to handle the inconsistency of multiple decisions in a decision table. In this algorithm, a greedy heuristic ‘misclassification error’ is used which performs faster, and for some cost function, results are better than ‘number of boundary subtables’ heuristic in literature. Therefore, it can be used in the case of larger data sets and does not require huge amount of memory. Experimental results of depth, average depth and number of nodes of decision trees constructed by this algorithm are compared in the framework of each of the three approaches.
None, None
2013-06-04
Methods, apparatus, and products are disclosed for thread selection during context switching on a plurality of compute nodes that includes: executing, by a compute node, an application using a plurality of threads of execution, including executing one or more of the threads of execution; selecting, by the compute node from a plurality of available threads of execution for the application, a next thread of execution in dependence upon power characteristics for each of the available threads; determining, by the compute node, whether criteria for a thread context switch are satisfied; and performing, by the compute node, the thread context switch if the criteria for a thread context switch are satisfied, including executing the next thread of execution.
Olsson, O.
2018-01-01
We present a novel heuristic derived from a probabilistic cost model for approximate N-body simulations. We show that this new heuristic can be used to guide tree construction towards higher quality trees with improved performance over current N-body codes. This represents an important step beyond the current practice of using spatial partitioning for N-body simulations, and enables adoption of a range of state-of-the-art algorithms developed for computer graphics applications to yield further improvements in N-body simulation performance. We outline directions for further developments and review the most promising such algorithms.
Prediction-based dynamic load-sharing heuristics
Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.
1993-01-01
The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.
Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.
Richie, Megan; Josephson, S Andrew
2018-01-01
Construct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained
International Nuclear Information System (INIS)
Yoo, Sua; Kowalok, Michael E; Thomadsen, Bruce R; Henderson, Douglass L
2003-01-01
We have developed an efficient treatment-planning algorithm for prostate implants that is based on region of interest (ROI) adjoint functions and a greedy heuristic. For this work, we define the adjoint function for an ROI as the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. This ratio is computed once for each seed position prior to the optimization process. Optimization is performed by a greedy heuristic that selects seed positions according to their ratio values. With this method, clinically acceptable treatment plans are obtained in less than 2 s. For comparison, a branch-and-bound method to solve a mixed integer-programming model took more than 50 min to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 1500. This attribute makes this algorithm suitable for intra-operative real-time treatment planning
Methodology and Implementation on DSP of Heuristic Multiuser DS/CDMA Detectors
Directory of Open Access Journals (Sweden)
Alex Miyamoto Mussi
2010-12-01
Full Text Available The growing number of users of mobile communications networks and the scarcity of the electromagnetic spectrum make the use of diversity techniques and detection/decoding efficient, such as the use of multiple antennas at the transmitter and/or receiver, multiuser detection (MuD – Multiuser Detection, among others, have an increasingly prominent role in the telecommunications landscape. This paper presents a design methodology based on digital signal processors (DSP – Digital Signal Processor with a view to the implementation of multiuser heuristics detectors in systems DS/CDMA (Direct Sequence Code Division Multiple Access. Heuristics detection techniques result in near-optimal performance in order to approach the performance of maximum-likelihood (ML. In this work, was employed the DSP development platform called the C6713 DSK, which is based in Texas TMS320C6713 processor. The heuristics techniques proposed are based on well established algorithms in the literature. The efficiency of the algorithms implemented in DSP has been evaluated numerically by computing the measure of bit error rate (BER. Finally, the feasibility of implementation in DSP could then be verified by comparing results from multiple Monte-Carlo simulation in Matlab, with those obtained from implementation on DSP. It also demonstrates the effective increase in performance and system capacity of DS/CDMA with the use of heuristic multiuser detection techniques, implemented directly in the DSP.
Argobots: A Lightweight Low-Level Threading and Tasking Framework
Energy Technology Data Exchange (ETDEWEB)
Seo, Sangmin; Amer, Abdelhalim; Balaji, Pavan; Bordage, Cyril; Bosilca, George; Brooks, Alex; Carns, Philip; Castello, Adrian; Genet, Damien; Herault, Thomas; Iwasaki, Shintaro; Jindal, Prateek; Kale, Laxmikant V.; Krishnamoorthy, Sriram; Lifflander, Jonathan; Lu, Huiwei; Meneses, Esteban; Snir, Marc; Sun, Yanhua; Taura, Kenjiro; Beckman, Pete
2018-03-01
In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, either are too specific to applications or architectures or are not as powerful or flexible. In this paper, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by end users or high-level programming models. We describe the design, implementation, and performance characterization of Argobots and present integrations with three high-level models: OpenMP, MPI, and colocated I/O services. Evaluations show that (1) Argobots, while providing richer capabilities, is competitive with existing simpler generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency-hiding capabilities; and (4) I/O services with Argobots reduce interference with colocated applications while achieving performance competitive with that of a Pthreads approach.
Argobots: A Lightweight Low-Level Threading and Tasking Framework
International Nuclear Information System (INIS)
Seo, Sangmin; Amer, Abdelhalim; Balaji, Pavan; Bordage, Cyril; Bosilca, George
2017-01-01
In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, are either too specific to applications or architectures or are not as powerful or flexible. In this article, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by the user or high-level programming model. Here, we describe the design, implementation, and optimization of Argobots and present integrations with three example high-level models: OpenMP, MPI, and co-located I/O service. Evaluations show that (1) Argobots outperforms existing generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency hiding capabilities; and (4) I/O service with Argobots reduces interference with co-located applications, achieving performance competitive with that of the Pthreads version.
A Review of Lightweight Thread Approaches for High Performance Computing
Energy Technology Data Exchange (ETDEWEB)
Castello, Adrian; Pena, Antonio J.; Seo, Sangmin; Mayo, Rafael; Balaji, Pavan; Quintana-Orti, Enrique S.
2016-09-12
High-level, directive-based solutions are becoming the programming models (PMs) of the multi/many-core architectures. Several solutions relying on operating system (OS) threads perfectly work with a moderate number of cores. However, exascale systems will spawn hundreds of thousands of threads in order to exploit their massive parallel architectures and thus conventional OS threads are too heavy for that purpose. Several lightweight thread (LWT) libraries have recently appeared offering lighter mechanisms to tackle massive concurrency. In order to examine the suitability of LWTs in high-level runtimes, we develop a set of microbenchmarks consisting of commonlyfound patterns in current parallel codes. Moreover, we study the semantics offered by some LWT libraries in order to expose the similarities between different LWT application programming interfaces. This study reveals that a reduced set of LWT functions can be sufficient to cover the common parallel code patterns and that those LWT libraries perform better than OS threads-based solutions in cases where task and nested parallelism are becoming more popular with new architectures.
X-ray measurement of residual stress on bolt threads
International Nuclear Information System (INIS)
Hagiwara, Masaya; Nakahara, Kanefumi; Yoshimoto, Isamu.
1989-01-01
This study deals with X-ray measurement of residual stress at the local area around the thread root of a bolt. Residual stress in the 0.5 mm x 5 mm area was measured using a method of stepped scanning and parabolic approximation. The conditions of measurement had been determined and evaluated through the preliminary measurement of compressive stress acting on the cylindrical surface. Furthermore, the fatigue strength estimated by applying the residual stress data to the previously presented hypothesis was compared with the experimental results. The main conclusions obtained were as follows: (1) The residual stress in a relatively small area on the cylindrical surface with large curvature can be measured by X-ray using a method of stepped scanning and parabolic approximation; (2) The compressive residual stress measured at the thread root was larger for the bolt manufactured by thread rolling after heat treatment than for one manufactured by thread rolling before heat treatment; (3) The distribution of residual stress along the axial direction from the thread root to the portion under crest did not represent remarkable change in its value; (4) The residual stress of a bolt was somewhat decreased by fatigue loading on the condition of low mean stress; (5) The fatigue strength estimated using residual stress data showed the tendency of experimental results well. (author)
On benchmarking Stochastic Global Optimization Algorithms
Hendrix, E.M.T.; Lancinskas, A.
2015-01-01
A multitude of heuristic stochastic optimization algorithms have been described in literature to obtain good solutions of the box-constrained global optimization problem often with a limit on the number of used function evaluations. In the larger question of which algorithms behave well on which
Practical algorithms for linear boolean-width
ten Brinke, C.B.; van Houten, F.J.P.; Bodlaender, H.L.
2015-01-01
In this paper, we give a number of new exact algorithms and heuristics to compute linear boolean decompositions, and experimentally evaluate these algorithms. The experimental evaluation shows that significant improvements can be made with respect to running time without increasing the width of the
Practical algorithms for linear Boolean-width
ten Brinke, C.B.; van Houten, F.J.P.; Bodlaender, H.L.
2015-01-01
In this paper, we give a number of new exact algorithms and heuristics to compute linear boolean decompositions, and experimentally evaluate these algorithms. The experimental evaluation shows that significant improvements can be made with respect to running time without increasing the width of the
Node fingerprinting: an efficient heuristic for aligning biological networks.
Radu, Alex; Charleston, Michael
2014-10-01
With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.
Doubravsky, Karel; Dohnal, Mirko
2015-01-01
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
Directory of Open Access Journals (Sweden)
Karel Doubravsky
Full Text Available Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (rechecked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.
Lecca, Paola
2018-01-01
We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of
Can we trust module-respect heuristics?
International Nuclear Information System (INIS)
Mo, Yuchang
2013-01-01
BDD (Binary Decision Diagrams) have proven to be a very efficient tool to assess Fault Trees. However, the size of BDD, and therefore the efficiency of the whole methodology, depends dramatically on the choice of variable ordering. The determination of the best variable ordering is intractable. Therefore, heuristics have been designed to select reasonably good variable orderings. One very important common feature for good static heuristics is to respect modules. In this paper, the notion of module-respect is studied in a systematic way. It is proved that under certain condition there always exists an optimal ordering that respects modules. This condition is that for each module there is always a smallest module BDD and each included module variable appears only once. On the other hand, it is shown that for the trees not satisfying the above sufficient condition the optimal orderings may not be able to be directly generated using module-respect heuristics, even when the shuffling strategy is used.
Judgment under Uncertainty: Heuristics and Biases.
Tversky, A; Kahneman, D
1974-09-27
This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
Theory and Algorithms for Global/Local Design Optimization
National Research Council Canada - National Science Library
Haftka, Raphael T
2004-01-01
... the component and overall design as well as on exploration of global optimization algorithms. In the former category, heuristic decomposition was followed with proof that it solves the original problem...
Creating and improving multi-threaded Geant4
Dong, Xin; Apostolakis, John; Jarp, Sverre; Nowak, Andrzej; Asai, Makoto; Brandt, Daniel
2012-01-01
We document the methods used to create the multi-threaded prototype Geant4MT from a sequential version of Geant4. We cover the Source-to-Source transformations applied, and discuss the process of verifying the correctness of the Geant4MT toolkit and applications based on it. Tools to ensure that the results of a transformed multi-threaded application are exactly equal to the original sequential version are under development. Stand-alone or simple applications can be adapted within 1-2 working days. Geant4MT is shown to scale linearly on an 80-core computer. In the special case of a single worker thread on one core, 30% overhead has been observed. We explain the reasons for this and the improvements introduced to reduce this overhead.
Heuristics for container loading of furniture
DEFF Research Database (Denmark)
Egeblad, Jens; Garavelli, Claudio; Lisi, Stefano
2010-01-01
. In the studied company, the problem arises hundreds of times daily during transport planning. Instances may contain more than one hundred different items with irregular shapes. To solve this complex problem we apply a set of heuristics successively that each solve one part of the problem. Large items...... are combined in specific structures to ensure proper protection of the items during transportation and to simplify the problem. The solutions generated by the heuristic has an average loading utilization of 91.3% for the most general instances with average running times around 100 seconds....
Heuristic extension of the Schwarzschild metric
International Nuclear Information System (INIS)
Espinosa, J.M.
1982-01-01
The Schwarzschild solution of Einstein's equations of gravitation has several singularities. It is known that the singularity at r = 2Gm/c 2 is only apparent, a result of the coordinates in which the solution was found. Paradoxical results occuring near the singularity show the system of coordinates is incomplete. We introduce a simple, two-dimensional metric with an apparent singularity that makes it incomplete. By a straightforward, heuristic procedure we extend and complete this simple metric. We then use the same procedure to give a heuristic derivation of the Kruskal system of coordinates, which is known to extend the Schwarzschild manifold past its apparent singularity and produce a complete manifold
Age Effects and Heuristics in Decision Making.
Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael
2012-05-01
Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects.
Development of Fire Resistant/Heat Resistant Sewing Thread
2016-03-01
BAA, specifically, Special Focus Area: Textile Technologies . Service Thread’s proposal is hereby accepted in its entirety by the government unless...report documents work carried out by Service Thread to show that domestic technology exists which would reduce base fiber costs, versus current...otherwise revised by this contract and is incorporated by reference. The technological area under investigation is FR/HR sewing threads using core
Large Scale Document Inversion using a Multi-threaded Computing System
Jung, Sungbo; Chang, Dar-Jen; Park, Juw Won
2018-01-01
Current microprocessor architecture is moving towards multi-core/multi-threaded systems. This trend has led to a surge of interest in using multi-threaded computing devices, such as the Graphics Processing Unit (GPU), for general purpose computing. We can utilize the GPU in computation as a massive parallel coprocessor because the GPU consists of multiple cores. The GPU is also an affordable, attractive, and user-programmable commodity. Nowadays a lot of information has been flooded into the digital domain around the world. Huge volume of data, such as digital libraries, social networking services, e-commerce product data, and reviews, etc., is produced or collected every moment with dramatic growth in size. Although the inverted index is a useful data structure that can be used for full text searches or document retrieval, a large number of documents will require a tremendous amount of time to create the index. The performance of document inversion can be improved by multi-thread or multi-core GPU. Our approach is to implement a linear-time, hash-based, single program multiple data (SPMD), document inversion algorithm on the NVIDIA GPU/CUDA programming platform utilizing the huge computational power of the GPU, to develop high performance solutions for document indexing. Our proposed parallel document inversion system shows 2-3 times faster performance than a sequential system on two different test datasets from PubMed abstract and e-commerce product reviews. CCS Concepts •Information systems➝Information retrieval • Computing methodologies➝Massively parallel and high-performance simulations.
Large Scale Document Inversion using a Multi-threaded Computing System.
Jung, Sungbo; Chang, Dar-Jen; Park, Juw Won
2017-06-01
Current microprocessor architecture is moving towards multi-core/multi-threaded systems. This trend has led to a surge of interest in using multi-threaded computing devices, such as the Graphics Processing Unit (GPU), for general purpose computing. We can utilize the GPU in computation as a massive parallel coprocessor because the GPU consists of multiple cores. The GPU is also an affordable, attractive, and user-programmable commodity. Nowadays a lot of information has been flooded into the digital domain around the world. Huge volume of data, such as digital libraries, social networking services, e-commerce product data, and reviews, etc., is produced or collected every moment with dramatic growth in size. Although the inverted index is a useful data structure that can be used for full text searches or document retrieval, a large number of documents will require a tremendous amount of time to create the index. The performance of document inversion can be improved by multi-thread or multi-core GPU. Our approach is to implement a linear-time, hash-based, single program multiple data (SPMD), document inversion algorithm on the NVIDIA GPU/CUDA programming platform utilizing the huge computational power of the GPU, to develop high performance solutions for document indexing. Our proposed parallel document inversion system shows 2-3 times faster performance than a sequential system on two different test datasets from PubMed abstract and e-commerce product reviews. •Information systems➝Information retrieval • Computing methodologies➝Massively parallel and high-performance simulations.
A heuristic for the inventory management of smart vending machine systems
Directory of Open Access Journals (Sweden)
Yang-Byung Park
2012-12-01
Full Text Available Purpose: The purpose of this paper is to propose a heuristic for the inventory management of smart vending machine systems with product substitution under the replenishment point, order-up-to level policy and to evaluate its performance.Design/methodology/approach: The heuristic is developed on the basis of the decoupled approach. An integer linear mathematical model is built to determine the number of product storage compartments and replenishment threshold for each smart vending machine in the system and the Clarke and Wright’s savings algorithm is applied to route vehicles for inventory replenishments of smart vending machines that share the same delivery days. Computational experiments are conducted on several small-size test problems to compare the proposed heuristic with the integrated optimization mathematical model with respect to system profit. Furthermore, a sensitivity analysis is carried out on a medium-size test problem to evaluate the effect of the customer service level on system profit using a computer simulation.Findings: The results show that the proposed heuristic yielded pretty good solutions with 5.7% error rate on average compared to the optimal solutions. The proposed heuristic took about 3 CPU minutes on average in the test problems being consisted of 10 five-product smart vending machines. It was confirmed that the system profit is significantly affected by the customer service level.Originality/value: The inventory management of smart vending machine systems is newly treated. Product substitutions are explicitly considered in the model. The proposed heuristic is effective as well as efficient. It can be easily modified for application to various retail vending settings under a vendor-managed inventory scheme with POS system.
PROBLEM SOLVING IN SCHOOL MATHEMATICS BASED ON HEURISTIC STRATEGIES
Directory of Open Access Journals (Sweden)
NOVOTNÁ, Jarmila
2014-03-01
Full Text Available The paper describes one of the ways of developing pupils’ creative approach to problem solving. The described experiment is a part of a longitudinal research focusing on improvement of culture of problem solving by pupils. It deals with solving of problems using the following heuristic strategies: Analogy, Guess – check – revise, Systematic experimentation, Problem reformulation, Solution drawing, Way back and Use of graphs of functions. Most attention is paid to the question whether short-term work, in this case only over the period of three months, can result in improvement of pupils’ abilities to solve problems whose solving algorithms are easily accessible. It also answers the question which strategies pupils will prefer and with what results. The experiment shows that even short-term work can bear positive results as far as pupils’ approach to problem solving is concerned.
A variable neighborhood descent based heuristic to solve the capacitated location-routing problem
Directory of Open Access Journals (Sweden)
M. S. Jabal-Ameli
2011-01-01
Full Text Available Location-routing problem (LRP is established as a new research area in the context of location analysis. The primary concern of LRP is on locating facilities and routing of vehicles among established facilities and existing demand points. In this work, we address the capacitated LRP which arises in many practical applications within logistics and supply chain management. The objective is to minimize the overall system costs which include the fixed costs of opening depots and using vehicles at each depot site, and the variable costs associated with delivery activities. A novel heuristic is proposed which is based on variable neighborhood descent (VND algorithm to solve the resulted problem. The computational study indicates that the proposed VND based heuristic is highly competitive with the existing solution algorithms in terms of solution quality.
Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning
Payne, Velma L.; Crowley, Rebecca S.
2008-01-01
We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as ca...
Automated generation of constructive ordering heuristics for educational timetabling
Pillay, Nelishia; Özcan, Ender
2017-01-01
Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics. For examination timetabling and university course timetabling problems essentially graph colouring heuristics have been used for this purpose. The process of deriving heuristics manually for educational timetabling is a time consuming task. Furthermor...
Adaptive selection of heuristics for improving exam timetables
Burke, Edmund; Qu, Rong; Soghier, Amr
2014-01-01
This paper presents a hyper-heuristic approach which hybridises low-level heuristic moves to improve timetables. Exams which cause a soft-constraint violation in the timetable are ordered and rescheduled to produce a better timetable. It is observed that both the order in which exams are rescheduled and the heuristic moves used to reschedule the exams and improve the timetable affect the quality of the solution produced. After testing different combinations in a hybrid hyper-heuristic approac...
Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation
Kia, Chua; Arshad, Mohd Rizal
2006-01-01
This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms and fuzzy inference system ...
Applying usability heuristics to radiotherapy systems
International Nuclear Information System (INIS)
Chan, Alvita J.; Islam, Mohammad K.; Rosewall, Tara; Jaffray, David A.; Easty, Anthony C.; Cafazzo, Joseph A.
2012-01-01
Background and purpose: Heuristic evaluations have been used to evaluate safety of medical devices by identifying and assessing usability issues. Since radiotherapy treatment delivery systems often consist of multiple complex user-interfaces, a heuristic evaluation was conducted to assess the potential safety issues of such a system. Material and methods: A heuristic evaluation was conducted to evaluate the treatment delivery system at Princess Margaret Hospital (Toronto, Canada). Two independent evaluators identified usability issues with the user-interfaces and rated the severity of each issue. Results: The evaluators identified 75 usability issues in total. Eighteen of them were rated as high severity, indicating the potential to have a major impact on patient safety. A majority of issues were found on the record and verify system, and many were associated with the patient setup process. While the hospital has processes in place to ensure patient safety, recommendations were developed to further mitigate the risks of potential consequences. Conclusions: Heuristic evaluation is an efficient and inexpensive method that can be successfully applied to radiotherapy delivery systems to identify usability issues and improve patient safety. Although this study was conducted only at one site, the findings may have broad implications for the design of these systems.
Can the inherence heuristic explain vitalistic reasoning?
Bastian, Brock
2014-10-01
Inherence is an important component of psychological essentialism. By drawing on vitalism as a way in which to explain this link, however, the authors appear to conflate causal explanations based on fixed features with those based on general causal forces. The disjuncture between these two types of explanatory principles highlights potential new avenues for the inherence heuristic.
Fast heuristics for a dynamic paratransit problem
Cremers, M.L.A.G.; Klein Haneveld, W.K.; van der Vlerk, M.H.
2008-01-01
In a previous paper we developed a non-standard two-stage recourse model for the dynamic day-ahead paratransit planning problem. Two heuristics, which are frequently applied in the recourse model, contain many details which leads to large CPU times to solve instances of relatively small size. In
A Heuristic for Improving Transmedia Exhibition Experience
DEFF Research Database (Denmark)
Selvadurai, Vashanth; Rosenstand, Claus Andreas Foss
2017-01-01
in the scientific field of designing transmedia experience in an exhibition context that links the pre- and post-activities to the actual visit (during-activities). The result of this study is a preliminary heuristic for establishing a relation between the platform and content complexity in transmedia exhibitions....
Heuristics for speeding up gaze estimation
DEFF Research Database (Denmark)
Leimberg, Denis; Vester-Christensen, Martin; Ersbøll, Bjarne Kjær
2005-01-01
A deformable template method for eye tracking on full face images is presented. The strengths of the method are that it is fast and retains accuracy independently of the resolution. We compare the method with a state of the art active contour approach, showing that the heuristic method is more...
The Heuristic Interpretation of Box Plots
Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim
2013-01-01
Box plots are frequently used, but are often misinterpreted by students. Especially the area of the box in box plots is often misinterpreted as representing number or proportion of observations, while it actually represents their density. In a first study, reaction time evidence was used to test whether heuristic reasoning underlies this…
Heuristic Classification. Technical Report Number 12.
Clancey, William J.
A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…
Engineering applications of heuristic multilevel optimization methods
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
A Heuristic for the Teaching of Persuasion.
Schell, John F.
Interpreting Aristotle's criteria for persuasive writing--ethos, logos, and pathos--as a concern for writer, language, and audience creates both an effective model for persuasive writing and a structure around which to organize discussions of relevant rhetorical issues. Use of this heuristic to analyze writing style, organization, and content…
Fourth Graders' Heuristic Problem-Solving Behavior.
Lee, Kil S.
1982-01-01
Eight boys and eight girls from a rural elementary school participated in the investigation. Specific heuristics were adopted from Polya; and the students selected represented two substages of Piaget's concrete operational stage. Five hypotheses were generated, based on observed results and the study's theoretical rationale. (MP)
Heuristic Decision Making in Network Linking
M.J.W. Harmsen - Van Hout (Marjolein); B.G.C. Dellaert (Benedict); P.J.J. Herings (Jean-Jacques)
2015-01-01
textabstractNetwork formation among individuals constitutes an important part of many OR processes, but relatively little is known about how individuals make their linking decisions in networks. This article provides an investigation of heuristic effects in individual linking decisions for
Investigating Heuristic Evaluation: A Case Study.
Goldman, Kate Haley; Bendoly, Laura
When museum professionals speak of evaluating a web site, they primarily mean formative evaluation, and by that they primarily mean testing the usability of the site. In the for-profit world, usability testing is a multi-million dollar industry, while non-profits often rely on far too few dollars to do too much. Hence, heuristic evaluation is one…
Internal Medicine residents use heuristics to estimate disease probability
Directory of Open Access Journals (Sweden)
Sen Phang
2015-12-01
Conclusions: Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.
Heuristics Made Easy: An Effort-Reduction Framework
Shah, Anuj K.; Oppenheimer, Daniel M.
2008-01-01
In this article, the authors propose a new framework for understanding and studying heuristics. The authors posit that heuristics primarily serve the purpose of reducing the effort associated with a task. As such, the authors propose that heuristics can be classified according to a small set of effort-reduction principles. The authors use this…
A Variable-Selection Heuristic for K-Means Clustering.
Brusco, Michael J.; Cradit, J. Dennis
2001-01-01
Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)
Heuristic Diagrams as a Tool to Teach History of Science
Chamizo, Jose A.
2012-01-01
The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The…
A Multi-threaded Version of Field II
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
2014-01-01
A multi-threaded version of Field II has been developed, which automatically can use the multi-core capabil- ities of modern CPUs. The memory allocation routines were rewritten to minimize the number of dynamic allocations and to make pre-allocations possible for each thread. This ensures...... that the simulation job can be automatically partitioned and the interdependence between threads minimized. The new code has been compared to Field II version 3.22, October 27, 2013 (latest free-ware version). A 64 element 5 MHz focused array transducer was simulated. One million point scatterers randomly distributed...... in a plane of 20 x 50 mm (width x depth) with random Gaussian amplitudes were simulated using the command calc scat . Dual Intel Xeon CPU E5-2630 2.60 GHz CPUs were used under Ubuntu Linux 10.02 and Matlab version 2013b. Each CPU holds 6 cores with hyper-threading, corresponding to a total of 24 hyper...
Weaving colourful threads: A tapestry of spirituality and mysticism
African Journals Online (AJOL)
2015-09-29
Sep 29, 2015 ... contributing to a discussion of these issues, it is hoped that the threads of spirituality and ... has been described as an 'applause-word'2 and is widely used in medicine, business, education, ..... of morality in teaching spirituality: 'If we as educators […] ..... William James ([1902] 1982), is worth quoting here:.
A Multi-Threaded Cryptographic Pseudorandom Number Generator Test Suite
2016-09-01
bitcoin thieves, Google releases patch. (2013, Aug. 16). SiliconANGLE. [Online]. Available: http://siliconangle.com/blog/2013/ 08/16/android-crypto-prng...flaw-aided- bitcoin -thieves-google-releases-patch/ [5] M. Gondree. (2014, Sep. 28). NPS POSIX thread pool library. [Online]. Available: https
The Automated Threaded Fastening Based on On-line Identification
Directory of Open Access Journals (Sweden)
Nicolas Ivan Giannoccaro
2008-11-01
Full Text Available The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.
Structural Analysis of Taper-Threaded Rebar Couplers
International Nuclear Information System (INIS)
Chu, Seok Jae; Kwon, Hyuk Mo; Seo, Sang Hwan
2014-01-01
A number of rebar couplers were developed by the leading companies. The information about the products is available from the company website. However, the theory on the taper-threaded coupler is not available. In this paper, the mechanics of the taper-thread was developed to understand the effect of the tightening torque. Structural analysis of our own newly developed rebar coupler was done to improve the strength of the coupler. The taper-threaded rebar coupler was analyzed. The tightening of the rebar into the coupler developed a circumferential stress in the coupler. The circumferential stress depends on the coefficient of friction as well as the tightening torque. The circumferential stress is less than the allowable stress 20 kgf/mm 2 of the material for the coefficient of friction greater than 0.1. The tightening of the rebar into the coupler and the subsequent tensioning was simulated using CATIA. Linear elastic analysis considering contact was done. The tightening of the taper-threaded rebar developed a uniform stress distribution in both standard coupler and position coupler. On the other hand, the tightening of the nut in the axial direction developed a non-uniform stress distribution. Similarly the tensioning also developed a non-uniform stress distribution
Hybrid Experiential-Heuristic Cognitive Radio Engine Architecture and Implementation
Directory of Open Access Journals (Sweden)
Ashwin Amanna
2012-01-01
Full Text Available The concept of cognitive radio (CR focuses on devices that can sense their environment, adapt configuration parameters, and learn from past behaviors. Architectures tend towards simplified decision-making algorithms inspired by human cognition. Initial works defined cognitive engines (CEs founded on heuristics, such as genetic algorithms (GAs, and case-based reasoning (CBR experiential learning algorithms. This hybrid architecture enables both long-term learning, faster decisions based on past experience, and capability to still adapt to new environments. This paper details an autonomous implementation of a hybrid CBR-GA CE architecture on a universal serial radio peripheral (USRP software-defined radio focused on link adaptation. Details include overall process flow, case base structure/retrieval method, estimation approach within the GA, and hardware-software lessons learned. Unique solutions to realizing the concept include mechanisms for combining vector distance and past fitness into an aggregate quantification of similarity. Over-the-air performance under several interference conditions is measured using signal-to-noise ratio, packet error rate, spectral efficiency, and throughput as observable metrics. Results indicate that the CE is successfully able to autonomously change transmit power, modulation/coding, and packet size to maintain the link while a non-cognitive approach loses connectivity. Solutions to existing shortcomings are proposed for improving case-base searching and performance estimation methods.
A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks
Directory of Open Access Journals (Sweden)
Kyung-Geun Lee
2013-06-01
Full Text Available Femtocells represent a novel configuration for existing cellular communication, contributing towards the improvement of coverage and throughput. The dense deployment of these femtocells causes significant femto-macro and femto-femto interference, consequently deteriorating the throughput of femtocells. In this study, we compare two heuristic approaches, i.e., particle swarm optimization (PSO and genetic algorithm (GA, for joint power assignment and resource allocation, within the context of the femtocell environment. The supposition made in this joint optimization is that the discrete power levels are available for the assignment. Furthermore, we have employed two variants of each PSO and GA: inertia weight and constriction factor model for PSO, and twopoint and uniform crossover for GA. The two proposed algorithms are in a decentralized manner, with no involvement of any centralized entity. The comparison is carried out between the two proposed algorithms for the aforementioned joint optimization problem. The contrast includes the performance metrics: including average objective function, min–max throughput of the femtocells, average throughput of the femto users, outage rate and time complexity. The results demonstrate that the decentralized PSO constriction factor outperforms the others in terms of the aforementioned performance metrics.
Neural model of gene regulatory network: a survey on supportive meta-heuristics.
Biswas, Surama; Acharyya, Sriyankar
2016-06-01
Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.
Heuristics structure and pervade formal risk assessment.
MacGillivray, Brian H
2014-04-01
Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art. © 2013 Society for Risk Analysis.
Energy-aware Thread and Data Management in Heterogeneous Multi-core, Multi-memory Systems
Energy Technology Data Exchange (ETDEWEB)
Su, Chun-Yi [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
2014-12-16
(NUMA) systems. I use critical path analysis to quantify memory contention in the NUMA memory system and determine thread mappings. In addition, I implement a runtime system that combines concurrent throttling and a novel thread mapping algorithm to manage thread resources and improve energy efficient execution in multi-core, NUMA systems.
Heuristic Evaluation of E-Learning Courses: A Comparative Analysis of Two E-Learning Heuristic Sets
Zaharias, Panagiotis; Koutsabasis, Panayiotis
2012-01-01
Purpose: The purpose of this paper is to discuss heuristic evaluation as a method for evaluating e-learning courses and applications and more specifically to investigate the applicability and empirical use of two customized e-learning heuristic protocols. Design/methodology/approach: Two representative e-learning heuristic protocols were chosen…
A derived heuristics based multi-objective optimization procedure for micro-grid scheduling
Li, Xin; Deb, Kalyanmoy; Fang, Yanjun
2017-06-01
With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.
Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong
2017-06-02
Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.
Identifying product development crises: The potential of adaptive heuristics
DEFF Research Database (Denmark)
Münzberger, C.; Stingl, Verena; Oehmen, Josef
2017-01-01
This paper introduces adaptive heuristics as a tool to identify crises in design projects and highlights potential applications of these heuristics as decision support tool for crisis identification. Crises may emerge slowly or suddenly, and often have ambiguous signals. Thus the identification...... for the application of heuristics in design sciences. To achieve this, the paper compares crises to 'business as usual', and presents sixteen indicators for emerging crises. These indicators are potential cues for adaptive heuristics. Specifically three adaptive heuristics, One-single-cue, Fast-and-Frugal-Trees...
Learning process mapping heuristics under stochastic sampling overheads
Ieumwananonthachai, Arthur; Wah, Benjamin W.
1991-01-01
A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.
Assessing the use of cognitive heuristic representativeness in clinical reasoning.
Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca
2008-11-06
We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.
Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning
Payne, Velma L.; Crowley, Rebecca S.
2008-01-01
We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140
Reconsidering "evidence" for fast-and-frugal heuristics.
Hilbig, Benjamin E
2010-12-01
In several recent reviews, authors have argued for the pervasive use of fast-and-frugal heuristics in human judgment. They have provided an overview of heuristics and have reiterated findings corroborating that such heuristics can be very valid strategies leading to high accuracy. They also have reviewed previous work that implies that simple heuristics are actually used by decision makers. Unfortunately, concerning the latter point, these reviews appear to be somewhat incomplete. More important, previous conclusions have been derived from investigations that bear some noteworthy methodological limitations. I demonstrate these by proposing a new heuristic and provide some novel critical findings. Also, I review some of the relevant literature often not-or only partially-considered. Overall, although some fast-and-frugal heuristics indeed seem to predict behavior at times, there is little to no evidence for others. More generally, the empirical evidence available does not warrant the conclusion that heuristics are pervasively used.
SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.
Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf
2015-08-01
RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.
SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics
Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf
2015-01-01
Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465
Tri-Level Optimization Algorithms for Solving Defender-Attacker-Defender Network Models
2016-06-01
not improved over three iterations of relaxation. In the heuristic , the current upper bound represents the best found feasible solution that does not...nested loops in the 167 algorithm which represent the outer and inner decompositions of the DAD CSP problem instance. Since our heuristic ...path problem. We merge the attacker model with Lagrangian relaxation of the operator model into a single formulation that can obtain fast heuristic
Directory of Open Access Journals (Sweden)
Tashkova Katerina
2011-10-01
Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of
Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo
2011-10-11
We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and
Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.
Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo
2016-07-19
Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .
Heuristics and Cognitive Error in Medical Imaging.
Itri, Jason N; Patel, Sohil H
2018-05-01
The field of cognitive science has provided important insights into mental processes underlying the interpretation of imaging examinations. Despite these insights, diagnostic error remains a major obstacle in the goal to improve quality in radiology. In this article, we describe several types of cognitive bias that lead to diagnostic errors in imaging and discuss approaches to mitigate cognitive biases and diagnostic error. Radiologists rely on heuristic principles to reduce complex tasks of assessing probabilities and predicting values into simpler judgmental operations. These mental shortcuts allow rapid problem solving based on assumptions and past experiences. Heuristics used in the interpretation of imaging studies are generally helpful but can sometimes result in cognitive biases that lead to significant errors. An understanding of the causes of cognitive biases can lead to the development of educational content and systematic improvements that mitigate errors and improve the quality of care provided by radiologists.
Heuristic program to design Relational Databases
Directory of Open Access Journals (Sweden)
Manuel Pereira Rosa
2009-09-01
Full Text Available The great development of today’s world determines that the world level of information increases day after day, however, the time allowed to transmit this information in the classrooms has not changed. Thus, the rational work in this respect is more than necessary. Besides, if for the solution of a given type of problem we do not have a working algorism, we have, first to look for a correct solution, then the heuristic programs are of paramount importance to succeed in these aspects. Having into consideration that the design of the database is, essentially, a process of problem resolution, this article aims at proposing a heuristic program for the design of the relating database.
Ansari, A H; Cherian, P J; Dereymaeker, A; Matic, V; Jansen, K; De Wispelaere, L; Dielman, C; Vervisch, J; Swarte, R M; Govaert, P; Naulaers, G; De Vos, M; Van Huffel, S
2016-09-01
After identifying the most seizure-relevant characteristics by a previously developed heuristic classifier, a data-driven post-processor using a novel set of features is applied to improve the performance. The main characteristics of the outputs of the heuristic algorithm are extracted by five sets of features including synchronization, evolution, retention, segment, and signal features. Then, a support vector machine and a decision making layer remove the falsely detected segments. Four datasets including 71 neonates (1023h, 3493 seizures) recorded in two different university hospitals, are used to train and test the algorithm without removing the dubious seizures. The heuristic method resulted in a false alarm rate of 3.81 per hour and good detection rate of 88% on the entire test databases. The post-processor, effectively reduces the false alarm rate by 34% while the good detection rate decreases by 2%. This post-processing technique improves the performance of the heuristic algorithm. The structure of this post-processor is generic, improves our understanding of the core visually determined EEG features of neonatal seizures and is applicable for other neonatal seizure detectors. The post-processor significantly decreases the false alarm rate at the expense of a small reduction of the good detection rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
High-Contention Mutual Exclusion by Elevator Algorithms
Buhr, Peter A.; Dice, Dave; Hesselink, Wim H.
2018-01-01
This paper presents new starvation-free hardware-assisted and software-only algorithms for the N-thread mutual-exclusion problem. The hardware-assisted versions use a single atomic-CAS instruction and no fences. The software-only algorithms simulate the CAS instruction using a variation of
Heuristic Evaluation for Novice Programming Systems
Kölling, Michael; McKay, Fraser
2016-01-01
The past few years has seen a proliferation of novice programming tools. The availability of a large number of systems has made it difficult for many users to choose among them. Even for education researchers, comparing the relative quality of these tools, or judging their respective suitability for a given context, is hard in many instances. For designers of such systems, assessing the respective quality of competing design decisions can be equally difficult.\\ud Heuristic evaluation provides...
Entrepreneurial Learning, Heuristics and Venture Creation
RAUF, MIAN SHAMS; ZAINULLAH, MOHAMMAD
2009-01-01
After rigorous criticism on trait approach and with the emergence of behavioral approach in entrepreneurship during 1980s, the researchers started to introduce learning and cognitive theories in entrepreneurship to describe and explain the dynamic nature of entrepreneurship. Many researchers have described venture creation as a core and the single most important element of entrepreneurship. This thesis will discuss and present the role of entrepreneurial learning and heuristics in venture cre...
The affect heuristic in occupational safety.
Savadori, Lucia; Caovilla, Jessica; Zaniboni, Sara; Fraccaroli, Franco
2015-07-08
The affect heuristic is a rule of thumb according to which, in the process of making a judgment or decision, people use affect as a cue. If a stimulus elicits positive affect then risks associated to that stimulus are viewed as low and benefits as high; conversely, if the stimulus elicits negative affect, then risks are perceived as high and benefits as low. The basic tenet of this study is that affect heuristic guides worker's judgment and decision making in a risk situation. The more the worker likes her/his organization the less she/he will perceive the risks as high. A sample of 115 employers and 65 employees working in small family agricultural businesses completed a questionnaire measuring perceived safety costs, psychological safety climate, affective commitment and safety compliance. A multi-sample structural analysis supported the thesis that safety compliance can be explained through an affect-based heuristic reasoning, but only for employers. Positive affective commitment towards their family business reduced employers' compliance with safety procedures by increasing the perceived cost of implementing them.
When decision heuristics and science collide.
Yu, Erica C; Sprenger, Amber M; Thomas, Rick P; Dougherty, Michael R
2014-04-01
The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.
The recognition heuristic: A decade of research
Directory of Open Access Journals (Sweden)
Gerd Gigerenzer
2011-02-01
Full Text Available The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein and Gigerenzer, 1999, 2002, including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.
Multi-thread Parallel Speech Recognition for Mobile Applications
Directory of Open Access Journals (Sweden)
LOJKA Martin
2014-05-01
Full Text Available In this paper, the server based solution of the multi-thread large vocabulary automatic speech recognition engine is described along with the Android OS and HTML5 practical application examples. The basic idea was to bring speech recognition available for full variety of applications for computers and especially for mobile devices. The speech recognition engine should be independent of commercial products and services (where the dictionary could not be modified. Using of third-party services could be also a security and privacy problem in specific applications, when the unsecured audio data could not be sent to uncontrolled environments (voice data transferred to servers around the globe. Using our experience with speech recognition applications, we have been able to construct a multi-thread speech recognition serverbased solution designed for simple applications interface (API to speech recognition engine modified to specific needs of particular application.
PHoToNs–A parallel heterogeneous and threads oriented code for cosmological N-body simulation
Wang, Qiao; Cao, Zong-Yan; Gao, Liang; Chi, Xue-Bin; Meng, Chen; Wang, Jie; Wang, Long
2018-06-01
We introduce a new code for cosmological simulations, PHoToNs, which incorporates features for performing massive cosmological simulations on heterogeneous high performance computer (HPC) systems and threads oriented programming. PHoToNs adopts a hybrid scheme to compute gravitational force, with the conventional Particle-Mesh (PM) algorithm to compute the long-range force, the Tree algorithm to compute the short range force and the direct summation Particle-Particle (PP) algorithm to compute gravity from very close particles. A self-similar space filling a Peano-Hilbert curve is used to decompose the computing domain. Threads programming is advantageously used to more flexibly manage the domain communication, PM calculation and synchronization, as well as Dual Tree Traversal on the CPU+MIC platform. PHoToNs scales well and efficiency of the PP kernel achieves 68.6% of peak performance on MIC and 74.4% on CPU platforms. We also test the accuracy of the code against the much used Gadget-2 in the community and found excellent agreement.
Tag SNP selection via a genetic algorithm.
Mahdevar, Ghasem; Zahiri, Javad; Sadeghi, Mehdi; Nowzari-Dalini, Abbas; Ahrabian, Hayedeh
2010-10-01
Single Nucleotide Polymorphisms (SNPs) provide valuable information on human evolutionary history and may lead us to identify genetic variants responsible for human complex diseases. Unfortunately, molecular haplotyping methods are costly, laborious, and time consuming; therefore, algorithms for constructing full haplotype patterns from small available data through computational methods, Tag SNP selection problem, are convenient and attractive. This problem is proved to be an NP-hard problem, so heuristic methods may be useful. In this paper we present a heuristic method based on genetic algorithm to find reasonable solution within acceptable time. The algorithm was tested on a variety of simulated and experimental data. In comparison with the exact algorithm, based on brute force approach, results show that our method can obtain optimal solutions in almost all cases and runs much faster than exact algorithm when the number of SNP sites is large. Our software is available upon request to the corresponding author.
Method of measuring misalignment of welded threaded connections
Energy Technology Data Exchange (ETDEWEB)
Kasatkin, V I
1981-01-01
A method is presented for measuring misalignment of welded connections by special attachment, superposed indicator. Requirements are analyzed for welding the threaded sleeves established by specifications. It is shown that measurement of the slack only in one section on the selected base is insufficient for monitoring the geometry of the connected pipe parts. It is suggested that in order to evaluate the misalignment the concept of total slack be used and formulas are derived to define it.
A PREDICTABLE MULTI-THREADED MAIN-MEMORY STORAGE MANAGER
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
This paper introduces the design and implementation of a predictable multi-threaded main-memo- ry storage manager (CS20), and emphasizes the database service mediator(DSM), an operation prediction model using exponential averaging. The memory manager, indexing, as well as lock manager in CS20 are also presented briefly. CS20 has been embedded in a mobile telecommunication service system. Practice showed, DSM effectively controls system load and hence improves the real-time characteristics of data accessing.
"The Gaze Heuristic:" Biography of an Adaptively Rational Decision Process.
Hamlin, Robert P
2017-04-01
This article is a case study that describes the natural and human history of the gaze heuristic. The gaze heuristic is an interception heuristic that utilizes a single input (deviation from a constant angle of approach) repeatedly as a task is performed. Its architecture, advantages, and limitations are described in detail. A history of the gaze heuristic is then presented. In natural history, the gaze heuristic is the only known technique used by predators to intercept prey. In human history the gaze heuristic was discovered accidentally by Royal Air Force (RAF) fighter command just prior to World War II. As it was never discovered by the Luftwaffe, the technique conferred a decisive advantage upon the RAF throughout the war. After the end of the war in America, German technology was combined with the British heuristic to create the Sidewinder AIM9 missile, the most successful autonomous weapon ever built. There are no plans to withdraw it or replace its guiding gaze heuristic. The case study demonstrates that the gaze heuristic is a specific heuristic type that takes a single best input at the best time (take the best 2 ). Its use is an adaptively rational response to specific, rapidly evolving decision environments that has allowed those animals/humans/machines who use it to survive, prosper, and multiply relative to those who do not. Copyright © 2017 Cognitive Science Society, Inc.
Compliant threads maximize spider silk connection strength and toughness
Meyer, Avery; Pugno, Nicola M.; Cranford, Steven W.
2014-01-01
Millions of years of evolution have adapted spider webs to achieve a range of functionalities, including the well-known capture of prey, with efficient use of material. One feature that has escaped extensive investigation is the silk-on-silk connection joints within spider webs, particularly from a structural mechanics perspective. We report a joint theoretical and computational analysis of an idealized silk-on-silk fibre junction. By modifying the theory of multiple peeling, we quantitatively compare the performance of the system while systematically increasing the rigidity of the anchor thread, by both scaling the stress–strain response and the introduction of an applied pre-strain. The results of our study indicate that compliance is a virtue—the more extensible the anchorage, the tougher and stronger the connection becomes. In consideration of the theoretical model, in comparison with rigid substrates, a compliant anchorage enormously increases the effective adhesion strength (work required to detach), independent of the adhered thread itself, attributed to a nonlinear alignment between thread and anchor (contact peeling angle). The results can direct novel engineering design principles to achieve possible load transfer from compliant fibre-to-fibre anchorages, be they silk-on-silk or another, as-yet undeveloped, system. PMID:25008083
Ion beam analysis of golden threads from Romanian medieval textiles
International Nuclear Information System (INIS)
Balta, Z.I.; Csedreki, L.; Furu, E.; Cretu, I.; Huszánk, R.; Lupu, M.; Török, Z.; Kertész, Z.; Szikszai, Z.
2015-01-01
In this study, metal threads from Romanian religious embroideries and precious velvet brocades dated from 15th to 18th century were analyzed by using IBA methods (PIXE and RBS) which, in comparison to the traditional analytical techniques (XRF, EDS), allowed the detection of their structures and accurate identification of the trace elements (detection limits of few tens of ppm). PIXE results confirmed that both types of the metal threads studied – wires and strips – have layered structures being made of fine silver, refined by cupellation, and gilded most probably with pure gold, and not of Au–Ag alloy, or gilded Ag–Cu alloy or Au–Ag–Cu alloy, as resulted from the previously performed SEM-EDS analysis. Trace elements of historical interest like lead, mercury and bismuth have been also possible to be detected by PIXE. The resulting elemental maps allowed us to identify the areas from which the metal thread structure and quantitative composition could be accurately determined. RBS measurements revealed that the gilding layer is separated from the silver bulk by an interface layer resulting through atomic diffusion of silver into the gold, which lead to the conclusion that the methods used for gilding were probably either the diffusion bonding or the fire gilding. The gilding layers thicknesses were estimated by PIXE with the GUPIX software and also determined from RBS measurements
Ion beam analysis of golden threads from Romanian medieval textiles
Energy Technology Data Exchange (ETDEWEB)
Balta, Z.I., E-mail: balta_z_i@yahoo.com [National History Museum of Romania, Calea Victoriei 12, Sector 3, Bucharest (Romania); Csedreki, L.; Furu, E. [Institute for Nuclear Research, Hungarian Academy of Sciences, H-4001 Debrecen, P.O. Box 51 (Hungary); Cretu, I. [National Art Museum of Romania, Calea Victoriei 49-53, Sector 1, Bucharest (Romania); Huszánk, R. [Institute for Nuclear Research, Hungarian Academy of Sciences, H-4001 Debrecen, P.O. Box 51 (Hungary); Lupu, M. [National Art Museum of Romania, Calea Victoriei 49-53, Sector 1, Bucharest (Romania); Török, Z.; Kertész, Z.; Szikszai, Z. [Institute for Nuclear Research, Hungarian Academy of Sciences, H-4001 Debrecen, P.O. Box 51 (Hungary)
2015-04-01
In this study, metal threads from Romanian religious embroideries and precious velvet brocades dated from 15th to 18th century were analyzed by using IBA methods (PIXE and RBS) which, in comparison to the traditional analytical techniques (XRF, EDS), allowed the detection of their structures and accurate identification of the trace elements (detection limits of few tens of ppm). PIXE results confirmed that both types of the metal threads studied – wires and strips – have layered structures being made of fine silver, refined by cupellation, and gilded most probably with pure gold, and not of Au–Ag alloy, or gilded Ag–Cu alloy or Au–Ag–Cu alloy, as resulted from the previously performed SEM-EDS analysis. Trace elements of historical interest like lead, mercury and bismuth have been also possible to be detected by PIXE. The resulting elemental maps allowed us to identify the areas from which the metal thread structure and quantitative composition could be accurately determined. RBS measurements revealed that the gilding layer is separated from the silver bulk by an interface layer resulting through atomic diffusion of silver into the gold, which lead to the conclusion that the methods used for gilding were probably either the diffusion bonding or the fire gilding. The gilding layers thicknesses were estimated by PIXE with the GUPIX software and also determined from RBS measurements.
Rapid and reliable protein structure determination via chemical shift threading.
Hafsa, Noor E; Berjanskii, Mark V; Arndt, David; Wishart, David S
2018-01-01
Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca .
Simulation of LHC events on a millions threads
Childers, J. T.; Uram, T. D.; LeCompte, T. J.; Papka, M. E.; Benjamin, D. P.
2015-12-01
Demand for Grid resources is expected to double during LHC Run II as compared to Run I; the capacity of the Grid, however, will not double. The HEP community must consider how to bridge this computing gap by targeting larger compute resources and using the available compute resources as efficiently as possible. Argonne's Mira, the fifth fastest supercomputer in the world, can run roughly five times the number of parallel processes that the ATLAS experiment typically uses on the Grid. We ported Alpgen, a serial x86 code, to run as a parallel application under MPI on the Blue Gene/Q architecture. By analysis of the Alpgen code, we reduced the memory footprint to allow running 64 threads per node, utilizing the four hardware threads available per core on the PowerPC A2 processor. Event generation and unweighting, typically run as independent serial phases, are coupled together in a single job in this scenario, reducing intermediate writes to the filesystem. By these optimizations, we have successfully run LHC proton-proton physics event generation at the scale of a million threads, filling two-thirds of Mira.
International Nuclear Information System (INIS)
Altarelli, F; Monasson, R; Zamponi, F
2008-01-01
We study the performances of stochastic heuristic search algorithms on Uniquely Extendible Constraint Satisfaction Problems with random inputs. We show that, for any heuristic preserving the Poissonian nature of the underlying instance, the (heuristic-dependent) largest ratio α a of constraints per variables for which a search algorithm is likely to find solutions is smaller than the critical ratio α d above which solutions are clustered and highly correlated. In addition we show that the clustering ratio can be reached when the number k of variables per constraints goes to infinity by the so-called Generalized Unit Clause heuristic
Security threads: effective security devices in the past, present, and future
Wolpert, Gary R.
2002-04-01
Security threads were first used to secure banknotes in the mid 1800's. The key to their anti-counterfeiting success was the fact that by being embedded in the paper, they became an integral part of the banknote substrate. Today, all major currencies still utilize this effective security feature. Technological developments have allowed security threads to evolve from a feature authenticated by only visual means to devices that incorporate both visual and machine detectable components. When viewed from the perspective of a thread being a carrier of various security technologies and the fact that they can be incorporated into the core substrate of banknotes, documents, labels, packaging and some high valued articles, it is clear that security threads will remain as effective security devices well into the future. This paper discusses a brief historical background of security threads, current visual and machine authentication technologies incorporated into threads today and a look to the future of threads as effective security devices.
International Nuclear Information System (INIS)
Tavares, R S; Tsuzuki, M S G; Martins, T C
2012-01-01
Electrical Impedance Tomography (EIT) is an imaging technique that attempts to reconstruct the conductivity distribution inside an object from electrical currents and potentials applied and measured at its surface. The EIT reconstruction problem is approached as an optimization problem, where the difference between the simulated and measured distributions must be minimized. This optimization problem can be solved using Simulated Annealing (SA), but at a high computational cost. To reduce the computational load, it is possible to use an incomplete evaluation of the objective function. This algorithm showed to present an outside-in behavior, determining the impedance of the external elements first, similar to a layer striping algorithm. A new outside-in heuristic to make use of this property is proposed. It also presents the impact of using GPU for parallelizing matrix-vector multiplication and triangular solvers. Results with experimental data are presented. The outside-in heuristic showed to be faster when compared to the conventional SA algorithm.
Directory of Open Access Journals (Sweden)
Christopher Expósito-Izquierdo
2017-02-01
Full Text Available This paper summarizes the main contributions of the Ph.D. thesis of Christopher Exp\\'osito-Izquierdo. This thesis seeks to develop a wide set of intelligent heuristic and meta-heuristic algorithms aimed at solving some of the most highlighted optimization problems associated with the transshipment and storage of containers at conventional maritime container terminals. Under the premise that no optimization technique can have a better performance than any other technique under all possible assumptions, the main point of interest in the domain of maritime logistics is to propose optimization techniques superior in terms of effectiveness and computational efficiency to previous proposals found in the scientific literature when solving individual optimization problems under realistic scenarios. Simultaneously, these optimization techniques should be enough competitive to be potentially implemented in practice. }}
Directory of Open Access Journals (Sweden)
Amir Salehipour
2012-01-01
Full Text Available This paper presents a novel application of operations research to support decision making in blood distribution management. The rapid and dynamic increasing demand, criticality of the product, storage, handling, and distribution requirements, and the different geographical locations of hospitals and medical centers have made blood distribution a complex and important problem. In this study, a real blood distribution problem containing 24 hospitals was tackled by the authors, and an exact approach was presented. The objective of the problem is to distribute blood and its products among hospitals and medical centers such that the total waiting time of those requiring the product is minimized. Following the exact solution, a hybrid heuristic algorithm is proposed. Computational experiments showed the optimal solutions could be obtained for medium size instances, while for larger instances the proposed hybrid heuristic is very competitive.
Liu, Weibo; Jin, Yan; Price, Mark
2016-10-01
A new heuristic based on the Nawaz-Enscore-Ham algorithm is proposed in this article for solving a permutation flow-shop scheduling problem. A new priority rule is proposed by accounting for the average, mean absolute deviation, skewness and kurtosis, in order to fully describe the distribution style of processing times. A new tie-breaking rule is also introduced for achieving effective job insertion with the objective of minimizing both makespan and machine idle time. Statistical tests illustrate better solution quality of the proposed algorithm compared to existing benchmark heuristics.
Cultural heuristics in risk assessment of HIV/AIDS.
Bailey, Ajay; Hutter, Inge
2006-01-01
Behaviour change models in HIV prevention tend to consider that risky sexual behaviours reflect risk assessments and that by changing risk assessments behaviour can be changed. Risk assessment is however culturally constructed. Individuals use heuristics or bounded cognitive devices derived from broader cultural meaning systems to rationalize uncertainty. In this study, we identify some of the cultural heuristics used by migrant men in Goa, India to assess their risk of HIV infection from different sexual partners. Data derives from a series of in-depth interviews and a locally informed survey. Cultural heuristics identified include visual heuristics, heuristics of gender roles, vigilance and trust. The paper argues that, for more culturally informed HIV/AIDS behaviour change interventions, knowledge of cultural heuristics is essential.
Data Clustering on Breast Cancer Data Using Firefly Algorithm with Golden Ratio Method
Directory of Open Access Journals (Sweden)
DEMIR, M.
2015-05-01
Full Text Available Heuristic methods are problem solving methods. In general, they obtain near-optimal solutions, and they do not take the care of provability of this case. The heuristic methods do not guarantee to obtain the optimal results; however, they guarantee to obtain near-optimal solutions in considerable time. In this paper, an application was performed by using firefly algorithm - one of the heuristic methods. The golden ratio was applied to different steps of firefly algorithm and different parameters of firefly algorithm to develop a new algorithm - called Firefly Algorithm with Golden Ratio (FAGR. It was shown that the golden ratio made firefly algorithm be superior to the firefly algorithm without golden ratio. At this aim, the developed algorithm was applied to WBCD database (breast cancer database to cluster data obtained from breast cancer patients. The highest obtained success rate among all executions is 96% and the highest obtained average success rate in all executions is 94.5%.
A grouping hyper-heuristic framework: application on graph colouring
Elhag, Anas; Özcan, Ender
2015-01-01
Grouping problems are hard to solve combinatorial optimisation problems which require partitioning of objects into a minimum number of subsets while a given objective is simultaneously optimised. Selection hyper-heuristics are high level general purpose search methodologies that operate on a space formed by a set of low level heuristics rather than solutions. Most of the recently proposed selection hyper-heuristics are iterative and make use of two key methods which are employed successively;...
Identifying Onboarding Heuristics for Free-to-Play Mobile Games
DEFF Research Database (Denmark)
Thomsen, Line Ebdrup; Weigert Petersen, Falko; Drachen, Anders
2016-01-01
a set of heuristics for the design of onboarding phases in mobile games is presented. The heuristics are identified by a lab-based mixed-methods experiment, utilizing lightweight psycho-physiological measures together with self-reported player responses, across three titles that cross the genres...... of puzzle games, base builders and arcade games, and utilize different onboarding phase design approaches. Results showcase how heuristics can be used to design engaging onboarding phases in mobile games....
The recognition heuristic : A review of theory and tests
Pachur, T.; Todd, P.; Gigerenzer, G.; Schooler, L.; Goldstein, D.
2011-01-01
The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) th...
Proposing New Heuristic Approaches for Preventive Maintenance Scheduling
Directory of Open Access Journals (Sweden)
majid Esmailian
2013-08-01
Full Text Available The purpose of preventive maintenance management is to perform a series of tasks that prevent or minimize production breakdowns and improve reliability of production facilities. An important objective of preventive maintenance management is to minimize downtime of production facilities. In order to accomplish this objective, personnel should efficiently allocate resources and determine an effective maintenance schedule. Gopalakrishnan (1997 developed a mathematical model and four heuristic approaches to solve the preventive maintenance scheduling problem of assigning skilled personnel to work with tasks that require a set of corresponding skills. However, there are several limitations in the prior work in this area of research. The craft combination problem has not been solved because the craft combination is assumed as given. The craft combination problem concerns the computation of all combinations of assigning multi skilled workers to accomplishment of a particular task. In fact, determining craft combinations is difficult because of the exponential number of craft combinations that are possible. This research provides a heuristic approach for determining the craft combination and four new heuristic approach solution for the preventive maintenance scheduling problem with multi skilled workforce constraints. In order to examine the new heuristic approach and to compare the new heuristic approach with heuristic approach of Gopalakrishnan (1997, 81 standard problems have been generated based on the criterion suggested by from Gopalakrishnan (1997. The average solution quality (SQ of the new heuristic approaches is 1.86% and in old heuristic approaches is 8.32%. The solution time of new heuristic approaches are shorter than old heuristic approaches. The solution time of new heuristic approaches is 0.78 second and old heuristic approaches is 6.43 second, but the solution time of mathematical model provided by Gopalakrishnan (1997 is 152 second.
A heuristic evaluation of the Facebook's advertising tool beacon
Jamal, A; Cole, M
2009-01-01
Interface usability is critical to the successful adoption of information systems. The aim of this study is to evaluate interface of Facebook's advertising tool Beacon by using privacy heuristics [4]. Beacon represents an interesting case study because of the negative media and user backlash it received. The findings of heuristic evaluation suggest violation of privacy heuristics [4]. Here, analysis identified concerns about user choice and consent, integrity and security of data, and awarene...
Interliminal Design: Understanding cognitive heuristics to mitigate design distortion
Andrew McCollough; DeAunne Denmark; Donald Harker
2014-01-01
Cognitive heuristics are mental shortcuts adapted over time to enable rapid interpretation of our complex environment. They are intrinsic to human cognition and resist modification. Heuristics applied outside the context to which they are best suited are termed cognitive bias, and are the cause of systematic errors in judgment and reasoning. As both a cognitive and intuitive discipline, design by individuals is vulnerable to context-inappropriate heuristic usage. Designing in groups can act p...
Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.
Lin, Lanny; Goodrich, Michael A
2014-12-01
During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem
Directory of Open Access Journals (Sweden)
Kanagasabai Lenin
2015-03-01
Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search
Directory of Open Access Journals (Sweden)
Xingwang Huang
2017-01-01
Full Text Available Binary bat algorithm (BBA is a binary version of the bat algorithm (BA. It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO. Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima.
Heuristic Portfolio Trading Rules with Capital Gain Taxes
DEFF Research Database (Denmark)
Fischer, Marcel; Gallmeyer, Michael
in some cases. Overlaying simple tax trading heuristics on these trading strategies improves out-of-sample performance. In particular, the 1/N trading strategy's welfare gains improve when a variety of tax trading heuristics are also imposed. For medium to large transaction costs, no trading strategy can...... outperform a 1/N trading strategy augmented with a tax heuristic, not even the most tax- and transaction-cost efficient buy-and-hold strategy. Overall, the best strategy is 1/N augmented with a heuristic that allows for a fixed deviation in absolute portfolio weights. Our results show that the best trading...
Intelligent process mapping through systematic improvement of heuristics
Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.
1992-01-01
The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.
Thread angle dependency on flame spread shape over kenaf/polyester combined fabric
Azahari Razali, Mohd; Sapit, Azwan; Nizam Mohammed, Akmal; Nor Anuar Mohamad, Md; Nordin, Normayati; Sadikin, Azmahani; Faisal Hushim, Mohd; Jaat, Norrizam; Khalid, Amir
2017-09-01
Understanding flame spread behavior is crucial to Fire Safety Engineering. It is noted that the natural fiber exhibits different flame spread behavior than the one of the synthetic fiber. This different may influences the flame spread behavior over combined fabric. There is a research has been done to examined the flame spread behavior over kenaf/polyester fabric. It is seen that the flame spread shape is dependent on the thread angle dependency. However, the explanation of this phenomenon is not described in detail in that research. In this study, explanation about this phenomenon is given in detail. Results show that the flame spread shape is dependent on the position of synthetic thread. For thread angle, θ = 0°, the polyester thread is breaking when the flame approach to the thread and the kenaf thread tends to move to the breaking direction. This behavior produces flame to be ‘V’ shape. However, for thread angle, θ = 90°, the polyester thread melts while the kenaf thread decomposed and burned. At this angle, the distance between kenaf threads remains constant as flame approaches.
Directory of Open Access Journals (Sweden)
Shangjun Ma
2015-01-01
Full Text Available Based on the differential principle of thread transmission, an analytical model considering helical directions between screw and roller threads in planetary roller screw mechanism (PRSM is presented in this work. The model is critical for the design of PRSM with a smaller lead and a bigger pitch to realize a higher transmission accuracy. The kinematic principle of planetary transmission is employed to analyze the PRSM with different screw thread and roller thread directions. In order to investigate the differences with different screw thread and roller thread directions, the numerical model is developed by using the software Adams to validate the analytical solutions calculated by the presented model. The results indicate, when the helical direction of screw thread is identical with the direction of roller thread, that the lead of PRSM is unaffected regardless of whether sliding between screw and rollers occurs or not. Only when the direction of screw thread is reverse to the direction of roller thread, the design of PRSM with a smaller lead can be realized under a bigger pitch. The presented models and numerical simulation method can be used to research the transmission accuracy of PRSM.
Using heuristic search for optimizing maintenance plans
International Nuclear Information System (INIS)
Mutanen, Teemu
2012-01-01
This work addresses the maintenance action selection process. Maintenance personnel need to evaluate maintenance actions and costs to keep the machines in working condition. Group of actions are evaluated together as maintenance plans. The maintenance plans as output provide information to the user about which actions to take if any and what future actions should be prepared for. The heuristic search method is implemented as part of general use toolbox for analysis of measurements from movable work machines. Impacts from machine's usage restrictions and maintenance activities are analysed. The results show that once put on a temporal perspective, the prioritized order of the actions is different and provide additional information to the user.
Efficient heuristics for the Rural Postman Problem
Directory of Open Access Journals (Sweden)
GW Groves
2005-06-01
Full Text Available A local search framework for the (undirected Rural Postman Problem (RPP is presented in this paper. The framework allows local search approaches that have been applied successfully to the well–known Travelling Salesman Problem also to be applied to the RPP. New heuristics for the RPP, based on this framework, are introduced and these are capable of solving significantly larger instances of the RPP than have been reported in the literature. Test results are presented for a number of benchmark RPP instances in a bid to compare efficiency and solution quality against known methods.
Heuristics for the Robust Coloring Problem
Directory of Open Access Journals (Sweden)
Miguel Ángel Gutiérrez Andrade
2011-03-01
Full Text Available Let $G$ and $\\bar{G}$ be complementary graphs. Given a penalty function defined on the edges of $G$, we will say that the rigidity of a $k$-coloring of $G$ is the sum of the penalties of the edges of G joining vertices of the same color. Based on the previous definition, the Robust Coloring Problem (RCP is stated as the search of the minimum rigidity $k$-coloring. In this work a comparison of heuristics based on simulated annealing, GRASP and scatter search is presented. These are the best results for the RCP that have been obtained.
Energy Technology Data Exchange (ETDEWEB)
Yoo, Sua [Department of Radiation Oncology, Duke University Medical Center, Box 3295, Durham, NC 27710 (United States); Kowalok, Michael E [Department of Radiation Oncology, Virginia Commonwealth University Health System, 401 College St., PO Box 980058, Richmond, VA 23298-0058 (United States); Thomadsen, Bruce R [Department of Medical Physics, University of Wisconsin-Madison, 1530 MSC, 1300 University Ave., Madison, WI 53706 (United States); Henderson, Douglass L [Department of Engineering Physics, University of Wisconsin-Madison, 153 Engineering Research Bldg., 1500 Engineering Dr., Madison, WI 53706 (United States)
2007-02-07
We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. Because seed positions are ranked in advance and because the greedy heuristic does not modify previously selected seed positions, the greedy heuristic constructs a complete seed configuration quickly. Isodose surface constraints determine the search space and the needle constraint limits the number of needles. This study additionally includes a methodology that scans possible combinations of these constraint values automatically. This automated selection scheme saves the user the effort of manually searching constraint values. With this method, clinically acceptable treatment plans are obtained in less than 2 min. For comparison, the branch-and-bound method used to solve a mixed integer-programming model took close to 2.5 h to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 100. This attribute makes this algorithm suitable for intra-operative real-time treatment planning.
International Nuclear Information System (INIS)
Yoo, Sua; Kowalok, Michael E; Thomadsen, Bruce R; Henderson, Douglass L
2007-01-01
We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. Because seed positions are ranked in advance and because the greedy heuristic does not modify previously selected seed positions, the greedy heuristic constructs a complete seed configuration quickly. Isodose surface constraints determine the search space and the needle constraint limits the number of needles. This study additionally includes a methodology that scans possible combinations of these constraint values automatically. This automated selection scheme saves the user the effort of manually searching constraint values. With this method, clinically acceptable treatment plans are obtained in less than 2 min. For comparison, the branch-and-bound method used to solve a mixed integer-programming model took close to 2.5 h to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 100. This attribute makes this algorithm suitable for intra-operative real-time treatment planning
Further heuristics for $k$-means: The merge-and-split heuristic and the $(k,l)$-means
Nielsen, Frank; Nock, Richard
2014-01-01
Finding the optimal $k$-means clustering is NP-hard in general and many heuristics have been designed for minimizing monotonically the $k$-means objective. We first show how to extend Lloyd's batched relocation heuristic and Hartigan's single-point relocation heuristic to take into account empty-cluster and single-point cluster events, respectively. Those events tend to increasingly occur when $k$ or $d$ increases, or when performing several restarts. First, we show that those special events ...
Comparison of greedy algorithms for α-decision tree construction
Alkhalid, Abdulaziz; Chikalov, Igor; Moshkov, Mikhail
2011-01-01
A comparison among different heuristics that are used by greedy algorithms which constructs approximate decision trees (α-decision trees) is presented. The comparison is conducted using decision tables based on 24 data sets from UCI Machine Learning Repository [2]. Complexity of decision trees is estimated relative to several cost functions: depth, average depth, number of nodes, number of nonterminal nodes, and number of terminal nodes. Costs of trees built by greedy algorithms are compared with minimum costs calculated by an algorithm based on dynamic programming. The results of experiments assign to each cost function a set of potentially good heuristics that minimize it. © 2011 Springer-Verlag.
Optimisation algorithms for ECG data compression.
Haugland, D; Heber, J G; Husøy, J H
1997-07-01
The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.
Algorithms for Academic Search and Recommendation Systems
DEFF Research Database (Denmark)
Amolochitis, Emmanouil
2014-01-01
are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...
Implementation of the ATLAS trigger within the ATLAS MultiThreaded Software Framework AthenaMT
Wynne, Benjamin; The ATLAS collaboration
2016-01-01
We present an implementation of the ATLAS High Level Trigger that provides parallel execution of trigger algorithms within the ATLAS multithreaded software framework, AthenaMT. This development will enable the ATLAS High Level Trigger to meet future challenges due to the evolution of computing hardware and upgrades of the Large Hadron Collider, LHC, and ATLAS Detector. During the LHC datataking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further, to up to 7.5 times the design value, in 2026 following LHC and ATLAS upgrades. This includes an upgrade of the ATLAS trigger architecture that will result in an increase in the High Level Trigger input rate by a factor of 4 to 10 compared to the current maximum rate of 100 kHz. The current ATLAS multiprocess framework, AthenaMP, manages a number of processes that process events independently, executing algorithms sequentially in each process. AthenaMT will provide a fully multithreaded env...
Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems
Petrovic, Sanja; Qu, Rong
2002-01-01
This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are dis...
Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method
Energy Technology Data Exchange (ETDEWEB)
Cao, Haibo [Iowa State Univ., Ames, IA (United States)
2003-01-01
In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.
Protein structure recognition: From eigenvector analysis to structural threading method
Cao, Haibo
In this work, we try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. We found a strong correlation between amino acid sequence and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, we give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part include discussions of interactions among amino acids residues, lattice HP model, and the designablity principle. In the second part, we try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in our eigenvector study of protein contact matrix. We believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, we discuss a threading method based on the correlation between amino acid sequence and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, we list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.
Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method
International Nuclear Information System (INIS)
Haibo Cao
2003-01-01
In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches
Atmospheric pressure H20 plasma treatment of polyester cord threads
International Nuclear Information System (INIS)
Simor, M.; Krump, H.; Hudec, I.; Rahel, J.; Brablec, A.; Cernak, M.
2004-01-01
Polyester cord threads, which are used as a reinforcing materials of rubber blend, have been treated in atmospheric-pressure H 2 0 plasma in order to enhance their adhesion to rubber. The atmospheric-pressure H 2 0 plasma was generated in an underwater diaphragm discharge. The plasma treatment resulted in approximately 100% improvement in the adhesion. Scanning electron microscopy investigation indicates that not only introduced surface polar groups but also increased surface area of the fibres due to a fibre surface roughening are responsible for the improved adhesive strength (Authors)
Implementation of the ATLAS trigger within the multi-threaded software framework AthenaMT
AUTHOR|(INSPIRE)INSPIRE-00225867; The ATLAS collaboration
2017-01-01
We present an implementation of the ATLAS High Level Trigger, HLT, that provides parallel execution of trigger algorithms within the ATLAS multithreaded software framework, AthenaMT. This development will enable the ATLAS HLT to meet future challenges due to the evolution of computing hardware and upgrades of the Large Hadron Collider, LHC, and ATLAS Detector. During the LHC data-taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further, to up to 7.5 times the design value, in 2026 following LHC and ATLAS upgrades. This includes an upgrade of the ATLAS trigger architecture that will result in an increase in the HLT input rate by a factor of 4 to 10 compared to the current maximum rate of 100 kHz. The current ATLAS multiprocess framework, AthenaMP, manages a number of processes that each execute algorithms sequentially for different events. AthenaMT will provide a fully multi-threaded environment that will additionally enable concurrent ...
CERN. Geneva
2016-01-01
Large scale scientific computing raises questions on different levels ranging from the fomulation of the problems to the choice of the best algorithms and their implementation for a specific platform. There are similarities in these different topics that can be exploited by modern-style C++ template metaprogramming techniques to produce readable, maintainable and generic code. Traditional low-level code tend to be fast but platform-dependent, and it obfuscates the meaning of the algorithm. On the other hand, object-oriented approach is nice to read, but may come with an inherent performance penalty. These lectures aim to present he basics of the Expression Template (ET) idiom which allows us to keep the object-oriented approach without sacrificing performance. We will in particular show to to enhance ET to include SIMD vectorization. We will then introduce techniques for abstracting iteration, and introduce thread-level parallelism for use in heavy data-centric loads. We will show to to apply these methods i...
Combined Heuristic Attack Strategy on Complex Networks
Directory of Open Access Journals (Sweden)
Marek Šimon
2017-01-01
Full Text Available Usually, the existence of a complex network is considered an advantage feature and efforts are made to increase its robustness against an attack. However, there exist also harmful and/or malicious networks, from social ones like spreading hoax, corruption, phishing, extremist ideology, and terrorist support up to computer networks spreading computer viruses or DDoS attack software or even biological networks of carriers or transport centers spreading disease among the population. New attack strategy can be therefore used against malicious networks, as well as in a worst-case scenario test for robustness of a useful network. A common measure of robustness of networks is their disintegration level after removal of a fraction of nodes. This robustness can be calculated as a ratio of the number of nodes of the greatest remaining network component against the number of nodes in the original network. Our paper presents a combination of heuristics optimized for an attack on a complex network to achieve its greatest disintegration. Nodes are deleted sequentially based on a heuristic criterion. Efficiency of classical attack approaches is compared to the proposed approach on Barabási-Albert, scale-free with tunable power-law exponent, and Erdős-Rényi models of complex networks and on real-world networks. Our attack strategy results in a faster disintegration, which is counterbalanced by its slightly increased computational demands.
Advances in heuristically based generalized perturbation theory
International Nuclear Information System (INIS)
Gandini, A.
1994-01-01
A distinctive feature of heuristically based generalized perturbation theory methodology consists in the systematic use of importance conservation concepts. As well known, this use leads to fundamental reciprocity relationship. Instead, the alternative variational and differential one approaches make a consistent use of the properties and adjoint functions. The equivalence between the importance and the adjoint functions have been demonstrated in important cases. There are some instances, however, in which the commonly known operator governing the adjoint function are not adequate. In this paper ways proposed to generalize this rules, as adopted with the heuristic generalized perturbation theory methodology, are illustrated. When applied to the neutron/nuclide field characterizing the core evolution in a power reactor system, in which also an intensive control variable (ρ) is defined, these rules leas to an orthogonality relationship connected to this same control variable. A set of ρ-mode eigenfunctions may be correspondingly defined and an extended concept of reactivity (generalizing that commonly associated with the multiplication factor) proposed as more directly indicative of the controllability of a critical reactor system. (author). 25 refs
A Geographical Heuristic Routing Protocol for VANETs
Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica
2016-01-01
Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254
Quantum Genetic Algorithms for Computer Scientists
Lahoz Beltrá, Rafael
2016-01-01
Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as “Quantum Geneti...
Scaling Sparse Matrices for Optimization Algorithms
Gajulapalli Ravindra S; Lasdon Leon S
2006-01-01
To iteratively solve large scale optimization problems in various contexts like planning, operations, design etc., we need to generate descent directions that are based on linear system solutions. Irrespective of the optimization algorithm or the solution method employed for the linear systems, ill conditioning introduced by problem characteristics or the algorithm or both need to be addressed. In [GL01] we used an intuitive heuristic approach in scaling linear systems that improved performan...
Hill climbing algorithms and trivium
DEFF Research Database (Denmark)
Borghoff, Julia; Knudsen, Lars Ramkilde; Matusiewicz, Krystian
2011-01-01
This paper proposes a new method to solve certain classes of systems of multivariate equations over the binary field and its cryptanalytical applications. We show how heuristic optimization methods such as hill climbing algorithms can be relevant to solving systems of multivariate equations....... A characteristic of equation systems that may be efficiently solvable by the means of such algorithms is provided. As an example, we investigate equation systems induced by the problem of recovering the internal state of the stream cipher Trivium. We propose an improved variant of the simulated annealing method...
Method for reinforcing threads in multilayer composite tubes and cylindrical structures
International Nuclear Information System (INIS)
Romanoski, G.R.; Burchell, T.D.
1996-01-01
Multilayer techniques such as: tape wrapping, braiding, and filament winding represent versatile and economical routes for fabricating composite tubes and cylindrical structures. However, multilayer architectures lack the radial reinforcement required to retain threads when the desired means of connection or closure is a threaded joint. This issue was addressed in the development of a filament wound, carbon-carbon composite impact shell for the NASA radioisotope thermoelectric generator. The problem of poor thread shear strength was solved by incorporating a number of radial elements of triangular geometry around the circumference of the thread for the full length of thread engagement. The radial elements significantly increased the shear strength of the threaded joint by transmitting the applied force to the balance of composite structure. This approach is also applicable to ceramic composites
Directory of Open Access Journals (Sweden)
Cojocaru Vasile
2014-06-01
Full Text Available In the thread root area of the threaded bolts submitted to axial loading occur local stresses, higher that nominal stresses calculated for the bolts. These local stresses can generate failure and can reduce the fatigue life of the parts. The paper is focused on the study of the influence of the thread root radius on the maximum local stresses. A large diameter trapezoidal bolt was subjected to a static analysis (axial loading using finite element simulation.
Geramizadeh, Maryam; Katoozian, Hamidreza; Amid, Reza; Kadkhodazadeh, Mahdi
2018-04-01
This study aimed to optimize the thread depth and pitch of a recently designed dental implant to provide uniform stress distribution by means of a response surface optimization method available in finite element (FE) software. The sensitivity of simulation to different mechanical parameters was also evaluated. A three-dimensional model of a tapered dental implant with micro-threads in the upper area and V-shaped threads in the rest of the body was modeled and analyzed using finite element analysis (FEA). An axial load of 100 N was applied to the top of the implants. The model was optimized for thread depth and pitch to determine the optimal stress distribution. In this analysis, micro-threads had 0.25 to 0.3 mm depth and 0.27 to 0.33 mm pitch, and V-shaped threads had 0.405 to 0.495 mm depth and 0.66 to 0.8 mm pitch. The optimized depth and pitch were 0.307 and 0.286 mm for micro-threads and 0.405 and 0.808 mm for V-shaped threads, respectively. In this design, the most effective parameters on stress distribution were the depth and pitch of the micro-threads based on sensitivity analysis results. Based on the results of this study, the optimal implant design has micro-threads with 0.307 and 0.286 mm depth and pitch, respectively, in the upper area and V-shaped threads with 0.405 and 0.808 mm depth and pitch in the rest of the body. These results indicate that micro-thread parameters have a greater effect on stress and strain values.
A proposed heuristic methodology for searching reloading pattern
International Nuclear Information System (INIS)
Choi, K. Y.; Yoon, Y. K.
1993-01-01
A new heuristic method for loading pattern search has been developed to overcome shortcomings of the algorithmic approach. To reduce the size of vast solution space, general shuffling rules, a regionwise shuffling method, and a pattern grouping method were introduced. The entropy theory was applied to classify possible loading patterns into groups with similarity between them. The pattern search program was implemented with use of the PROLOG language. A two-group nodal code MEDIUM-2D was used for analysis of power distribution in the core. The above mentioned methodology has been tested to show effectiveness in reducing of solution space down to a few hundred pattern groups. Burnable poison rods were then arranged in each pattern group in accordance with burnable poison distribution rules, which led to further reduction of the solution space to several scores of acceptable pattern groups. The method of maximizing cycle length (MCL) and minimizing power-peaking factor (MPF) were applied to search for specific useful loading patterns from the acceptable pattern groups. Thus, several specific loading patterns that have low power-peaking factor and large cycle length were successfully searched from the selected pattern groups. (Author)
Modelling antibody side chain conformations using heuristic database search.
Ritchie, D W; Kemp, G J
1997-01-01
We have developed a knowledge-based system which models the side chain conformations of residues in the variable domains of antibody Fv fragments. The system is written in Prolog and uses an object-oriented database of aligned antibody structures in conjunction with a side chain rotamer library. The antibody database provides 3-dimensional clusters of side chain conformations which can be copied en masse into the model structure. The object-oriented database architecture facilitates a navigational style of database access, necessary to assemble side chains clusters. Around 60% of the model is built using side chain clusters and this eliminates much of the combinatorial complexity associated with many other side chain placement algorithms. Construction and placement of side chain clusters is guided by a heuristic cost function based on a simple model of side chain packing interactions. Even with a simple model, we find that a large proportion of side chain conformations are modelled accurately. We expect our approach could be used with other homologous protein families, in addition to antibodies, both to improve the quality of model structures and to give a "smart start" to the side chain placement problem.
Heuristic Method for Decision-Making in Common Scheduling Problems
Directory of Open Access Journals (Sweden)
Edyta Kucharska
2017-10-01
Full Text Available The aim of the paper is to present a heuristic method for decision-making regarding an NP-hard scheduling problem with limitations related to tasks and the resources dependent on the current state of the process. The presented approach is based on the algebraic-logical meta-model (ALMM, which enables making collective decisions in successive process stages, not separately for individual objects or executors. Moreover, taking into account the limitations of the problem, it involves constructing only an acceptable solution and significantly reduces the amount of calculations. A general algorithm based on the presented method is composed of the following elements: preliminary analysis of the problem, techniques for the choice of decision at a given state, the pruning non-perspective trajectory, selection technique of the initial state for the trajectory final part, and the trajectory generation parameters modification. The paper includes applications of the presented approach to scheduling problems on unrelated parallel machines with a deadline and machine setup time dependent on the process state, where the relationship between tasks is defined by the graph. The article also presents the results of computational experiments.
Evolutionary Algorithms For Neural Networks Binary And Real Data Classification
Directory of Open Access Journals (Sweden)
Dr. Hanan A.R. Akkar
2015-08-01
Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.
Use of Statistical Heuristics in Everyday Inductive Reasoning.
Nisbett, Richard E.; And Others
1983-01-01
In everyday reasoning, people use statistical heuristics (judgmental tools that are rough intuitive equivalents of statistical principles). Use of statistical heuristics is more likely when (1) sampling is clear, (2) the role of chance is clear, (3) statistical reasoning is normative for the event, or (4) the subject has had training in…
A Priori Knowledge and Heuristic Reasoning in Architectural Design.
Rowe, Peter G.
1982-01-01
It is proposed that the various classes of a priori knowledge incorporated in heuristic reasoning processes exert a strong influence over architectural design activity. Some design problems require exercise of some provisional set of rules, inference, or plausible strategy which requires heuristic reasoning. A case study illustrates this concept.…
Refining a Heuristic for Constructing Bayesian Networks from Structured Arguments
Wieten, G.M.; Bex, F.J.; van der Gaag, L.C.; Prakken, H.; Renooij, S.
2018-01-01
Recently, a heuristic was proposed for constructing Bayesian networks (BNs) from structured arguments. This heuristic helps domain experts who are accustomed to argumentation to transform their reasoning into a BN and subsequently weigh their case evidence in a probabilistic manner. While the
Heuristic Inquiry: A Personal Journey of Acculturation and Identity Reconstruction
Djuraskovic, Ivana; Arthur, Nancy
2010-01-01
Heuristic methodology attempts to discover the nature and meaning of phenomenon through internal self-search, exploration, and discovery. Heuristic methodology encourages the researcher to explore and pursue the creative journey that begins inside one's being and ultimately uncovers its direction and meaning through internal discovery (Douglass &…
Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.
Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique
2016-01-01
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems.
Proximity search heuristics for wind farm optimal layout
DEFF Research Database (Denmark)
Fischetti, Martina; Monaci, Michele
2016-01-01
A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently...
Fairness and other leadership heuristics: A four-nation study
Janson, A.; Levy, L.; Sitkin, S.B.; Lind, E.A.
2008-01-01
Leaders' fairness may be just one of several heuristics - cognitive shortcuts - that followers use to decide quickly whether they can rely on a given leader to lead them to ends that are good for the collective, rather than just good for the leader. Other leadership heuristics might include leader
On Dual Processing and Heuristic Approaches to Moral Cognition
Lapsley, Daniel K.; Hill, Patrick L.
2008-01-01
We examine the implications of dual-processing theories of cognition for the moral domain, with particular emphasis upon "System 1" theories: the Social Intuitionist Model (Haidt), moral heuristics (Sunstein), fast-and-frugal moral heuristics (Gigerenzer), schema accessibility (Lapsley & Narvaez) and moral expertise (Narvaez). We argue that these…
Efficient Heuristics for Simulating Population Overflow in Parallel Networks
Zaburnenko, T.S.; Nicola, V.F.
2006-01-01
In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for costly optimization involved in other
Swift and Smart Decision Making: Heuristics that Work
Hoy, Wayne K.; Tarter, C. J.
2010-01-01
Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…
Does the inherence heuristic take us to psychological essentialism?
Marmodoro, Anna; Murphy, Robin A; Baker, A G
2014-10-01
We argue that the claim that essence-based causal explanations emerge, hydra-like, from an inherence heuristic is incomplete. No plausible mechanism for the transition from concrete properties, or cues, to essences is provided. Moreover, the fundamental shotgun and storytelling mechanisms of the inherence heuristic are not clearly enough specified to distinguish them, developmentally, from associative or causal networks.
Directory of Open Access Journals (Sweden)
Alexander Safatli
2015-06-01
Full Text Available Summary. Pylogeny is a cross-platform library for the Python programming language that provides an object-oriented application programming interface for phylogenetic heuristic searches. Its primary function is to permit both heuristic search and analysis of the phylogenetic tree search space, as well as to enable the design of novel algorithms to search this space. To this end, the framework supports the structural manipulation of phylogenetic trees, in particular using rearrangement operators such as NNI, SPR, and TBR, the scoring of trees using parsimony and likelihood methods, the construction of a tree search space graph, and the programmatic execution of a few existing heuristic programs. The library supports a range of common phylogenetic file formats and can be used for both nucleotide and protein data. Furthermore, it is also capable of supporting GPU likelihood calculation on nucleotide character data through the BEAGLE library.Availability. Existing development and source code is available for contribution and for download by the public from GitHub (http://github.com/AlexSafatli/Pylogeny. A stable release of this framework is available for download through PyPi (Python Package Index at http://pypi.python.org/pypi/pylogeny.
Directory of Open Access Journals (Sweden)
Diego Tami
2018-01-01
Full Text Available We discuss three sets of heuristic coefficients used in uniform theory of diffraction (UTD to characterize the electromagnetic scattering in realistic urban scenarios and canonical examples of diffraction by lossy conducting wedges using the three sets of heuristic coefficients and the Malyuzhinets solution as reference model. We compare not only the results of the canonical models but also their implementation in real outdoor scenarios. To predict the coverage of mobile networks, we used propagation models for outdoor environments by using a 3D ray-tracing model based on a brute-force algorithm for ray launching and a propagation model based on image theory. To evaluate each set of coefficients, we analyzed the mean and standard deviation of the absolute error between estimates and measured data in Ottawa, Canada; Valencia, Spain; and Cali, Colombia. Finally, we discuss the path loss prediction for each set of heuristic UTD coefficients in outdoor environment, as well as the comparison with the canonical results.
Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling
Burke, Edmund; MacCarthy, Bart L.; Petrovic, Sanja; Qu, Rong
2002-01-01
This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we main...
MAGNETOHYDRODYNAMIC WAVES IN A PARTIALLY IONIZED FILAMENT THREAD
International Nuclear Information System (INIS)
Soler, R.; Oliver, R.; Ballester, J. L.
2009-01-01
Oscillations and propagating waves are commonly seen in high-resolution observations of filament threads, i.e., the fine-structures of solar filaments/prominences. Since the temperature of prominences is typically of the order of 10 4 K, the prominence plasma is only partially ionized. In this paper, we study the effect of neutrals on the wave propagation in a filament thread modeled as a partially ionized homogeneous magnetic flux tube embedded in an homogeneous and fully ionized coronal plasma. Ohmic and ambipolar magnetic diffusion are considered in the basic resistive magnetohydrodynamic (MHD) equations. We numerically compute the eigenfrequencies of kink, slow, and Alfven linear MHD modes and obtain analytical approximations in some cases. We find that the existence of propagating modes is constrained by the presence of critical values of the longitudinal wavenumber. In particular, the lower and upper frequency cutoffs of kink and Alfven waves owe their existence to magnetic diffusion parallel and perpendicular to magnetic field lines, respectively. The slow mode only has a lower frequency cutoff, which is caused by perpendicular magnetic diffusion and is significantly affected by the ionization degree. In addition, ion-neutral collision is the most efficient damping mechanism for short wavelengths, while ohmic diffusion dominates in the long-wavelength regime.