Heuristic estimates in shortest path algorithms
W.H.L.M. Pijls (Wim)
2007-01-01
textabstractShortest path problems occupy an important position in operations research as well as in artificial intelligence. In this paper we study shortest path algorithms that exploit heuristic estimates. The well-known algorithms are put into one framework. Besides, we present an interesting
Heuristic estimates in shortest path algorithms
W.H.L.M. Pijls (Wim)
2006-01-01
textabstractShortest path problems occupy an important position in Operations Research as well as in Arti¯cial Intelligence. In this paper we study shortest path algorithms that exploit heuristic estimates. The well-known algorithms are put into one framework. Besides we present an interesting
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 ...
Heuristic Kalman algorithm for solving optimization problems.
Toscano, Rosario; Lyonnet, Patrick
2009-10-01
The main objective of this paper is to present a new optimization approach, which we call heuristic Kalman algorithm (HKA). We propose it as a viable approach for solving continuous nonconvex optimization problems. The principle of the proposed approach is to consider explicitly the optimization problem as a measurement process designed to produce an estimate of the optimum. A specific procedure, based on the Kalman method, was developed to improve the quality of the estimate obtained through the measurement process. The efficiency of HKA is evaluated in detail through several nonconvex test problems, both in the unconstrained and constrained cases. The results are then compared to those obtained via other metaheuristics. These various numerical experiments show that the HKA has very interesting potentialities for solving nonconvex optimization problems, notably concerning the computation time and the success ratio.
Nghia, Nguyen Duc; Binh, Huynh Thi Thanh
2008-01-01
We have introduced the heuristic algorithm for solving BDMST problem, called CBRC. The experiment shows that CBRC have best result than the other known heuristic algorithm for solving BDMST prolem on Euclidean instances. The best solution found by the genetic algorithm which uses best heuristic algorithm or only one heuristic algorithm for initialization the population is not better than the best solution found by the genetic algorithm which uses mixed heuristic algorithms (randomized heurist...
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.
Benchmarking Heuristic Search and Optimisation Algorithms in Matlab
Luo, Wuqiao; Li, Yun
2016-01-01
With the proliferating development of heuristic methods, it has become challenging to choose the most suitable ones for an application at hand. This paper evaluates the performance of these algorithms available in Matlab, as it is problem dependent and parameter sensitive. Further, the paper attempts to address the challenge that there exists no satisfied benchmarks to evaluation all the algorithms at the same standard. The paper tests five heuristic algorithms in Matlab, the Nelder-Mead simp...
A quantum heuristic algorithm for the traveling salesman problem
Bang, Jeongho; Ryu, Junghee; Lee, Changhyoup; Yoo, Seokwon; Lim, James; Lee, Jinhyoung
2012-12-01
We propose a quantum heuristic algorithm to solve the traveling salesman problem by generalizing the Grover search. Sufficient conditions are derived to greatly enhance the probability of finding the tours with the cheapest costs reaching almost to unity. These conditions are characterized by the statistical properties of tour costs and are shown to be automatically satisfied in the large-number limit of cities. In particular for a continuous distribution of the tours along the cost, we show that the quantum heuristic algorithm exhibits a quadratic speedup compared to its classical heuristic algorithm.
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.
New Heuristic Algorithm for Dynamic Traffic in WDM Optical Networks
Directory of Open Access Journals (Sweden)
Arturo Benito Rodríguez Garcia
2015-12-01
Full Text Available The results and comparison of the simulation of a new heuristic algorithm called Snake One are presented. The comparison is made with three heuristic algorithms, Genetic Algorithms, Simulated Annealing, and Tabu Search, using blocking probability and network utilization as standard indicators. The simulation was made on the WDM NSFNET under dynamic traffic conditions. The results show a substantial decrease of blocking, but this causes a relative growth of network utilization. There are also load intervals at which its performance improves, decreasing the number of blocked requests.
Meta-heuristic algorithms as tools for hydrological science
Yoo, Do Guen; Kim, Joong Hoon
2014-12-01
In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.
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.
A direct heuristic algorithm for linear programming
Indian Academy of Sciences (India)
The simplex method [6, 23] ± an exponential time (non-polynomial time) algorithm ± or its variation has been used and is being used to solve almost any linear programming problem (LPP) for the last four decades. In 1979, Khachiyan proposed the ellipsoid method ± the first polynomial-time (interior-point) algorithm ± to ...
A novel heuristic algorithm for capacitated vehicle routing problem
Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre
2017-02-01
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.
Heuristic-based scheduling algorithm for high level synthesis
Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye
1992-01-01
A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.
A NEW HEURISTIC ALGORITHM FOR MULTIPLE TRAVELING SALESMAN PROBLEM
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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.
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.
Two-Stage Heuristic Algorithm for Aircraft Recovery Problem
Directory of Open Access Journals (Sweden)
Cheng Zhang
2017-01-01
Full Text Available This study focuses on the aircraft recovery problem (ARP. In real-life operations, disruptions always cause schedule failures and make airlines suffer from great loss. Therefore, the main objective of the aircraft recovery problem is to minimize the total recovery cost and solve the problem within reasonable runtimes. An aircraft recovery model (ARM is proposed herein to formulate the ARP and use feasible line of flights as the basic variables in the model. We define the feasible line of flights (LOFs as a sequence of flights flown by an aircraft within one day. The number of LOFs exponentially grows with the number of flights. Hence, a two-stage heuristic is proposed to reduce the problem scale. The algorithm integrates a heuristic scoring procedure with an aggregated aircraft recovery model (AARM to preselect LOFs. The approach is tested on five real-life test scenarios. The computational results show that the proposed model provides a good formulation of the problem and can be solved within reasonable runtimes with the proposed methodology. The two-stage heuristic significantly reduces the number of LOFs after each stage and finally reduces the number of variables and constraints in the aircraft recovery model.
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
AliquotG: an improved heuristic algorithm for genome aliquoting.
Directory of Open Access Journals (Sweden)
Zelin Chen
Full Text Available An extant genome can be the descendant of an ancient polyploid genome. The genome aliquoting problem is to reconstruct the latter from the former such that the rearrangement distance (i.e., the number of genome rearrangements necessary to transform the former into the latter is minimal. Though several heuristic algorithms have been published, here, we sought improved algorithms for the problem with respect to the double cut and join (DCJ distance. The new algorithm makes use of partial and contracted partial graphs, and locally minimizes the distance. Our test results with simulation data indicate that it reliably recovers gene order of the ancestral polyploid genome even when the ancestor is ancient. We also compared the performance of our method with an earlier method using simulation data sets and found that our algorithm has higher accuracy. It is known that vertebrates had undergone two rounds of whole-genome duplication (2R-WGD during early vertebrate evolution. We used the new algorithm to calculate the DCJ distance between three modern vertebrate genomes and their 2R-WGD ancestor and found that the rearrangement rate might have slowed down significantly since the 2R-WGD. The software AliquotG implementing the algorithm is available as an open-source package from our website (http://mosas.sysu.edu.cn/genome/download_softwares.php.
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.
Page, Andrew J.; Keane, Thomas M.; Naughton, Thomas J.
2010-01-01
We present a multi-heuristic evolutionary task allocation algorithm to dynamically map tasks to processors in a heterogeneous distributed system. It utilizes a genetic algorithm, combined with eight common heuristics, in an effort to minimize the total execution time. It operates on batches of unmapped tasks and can preemptively remap tasks to processors. The algorithm has been implemented on a Java distributed system and evaluated with a set of six problems from the areas of bioinformatics, biomedical engineering, computer science and cryptography. Experiments using up to 150 heterogeneous processors show that the algorithm achieves better efficiency than other state-of-the-art heuristic algorithms. PMID:20862190
Using Heuristic Algorithms to Optimize Observing Target Sequences
Sosnowska, D.; Ouadahi, A.; Buchschacher, N.; Weber, L.; Pepe, F.
2014-05-01
The preparation of observations is normally carried out at the telescope by the visiting observer. In order to help the observer, we propose several algorithms to automatically optimize the sequence of targets. The optimization consists of assuring that all the chosen targets are observable within the given time interval, and to find their best execution order in terms of the observation quality and the shortest telescope displacement time. Since an exhaustive search is too expensive in time, we researched heuristic algorithms, specifically: Min-Conflict, Non-Sorting Genetic Algorithms and Simulated Annealing. Multiple metaheuristics are used in parallel to swiftly give an approximation of the best solution, with all the constraints satisfied and the total execution time minimized. The optimization process has a duration on the order of tens of seconds, allowing for quick re-adaptation in case of changing atmospheric conditions. The graphical user interface allows the user to control the parameters of the optimization process. Therefore, the search can be adjusted in real time. The module was coded in a way to allow easily the addition of new constraints, and thus ensure its compatibility with different instruments. For now, the application runs as a plug-in to the observation preparation tool called New Short Term Scheduler, which is used on three spectrographs dedicated to the exoplanets search: HARPS at the La Silla observatory, HARPS North at the La Palma observatory and SOPHIE at the Observatoire de Haute-Provence.
A fast heuristic algorithm for a probe mapping problem.
Mumey, B
1997-01-01
A new heuristic algorithm is presented for mapping probes to locations along the genome, given noisy pairwise distance data as input. The model considered is quite general: The input consists of a collection of probe pairs and a confidence interval for the genomic distance separating each pair. Because the distance intervals are only known with some confidence level, some may be erroneous and must be removed in order to find a consistent map. A novel randomized technique for detecting and removing bad distance intervals is described. The technique could be useful in other contexts where partially erroneous data is inconsistent with the remaining data. These algorithms were motivated by the goal of making probe maps with inter-probe distance confidence intervals estimated from fluorescence in-situ hybridization (FISH) experiments. Experimentation was done on synthetic data sets (with and without errors) and FISH data from a region of human chromosome 4. Problems with up to 100 probes could be solved in several minutes on a fast workstation. In addition to FISH mapping, we describe some other possible applications that fall within the problem model. These include: mapping a backbone structure in folded DNA, finding consensus maps between independent maps covering the same genomic region, and ordering clones in a clone library.
Directory of Open Access Journals (Sweden)
Dmitri A. VIATTCHENIN
2014-12-01
Full Text Available The paper deals with the problem of automatic labeling output variables in Mamdani-type fuzzy rules generated by using heuristic algorithms of possibilistic clustering. The labeling problem in fuzzy clustering and basic concepts the heuristic approach to possibilistic clustering are considered in brief. Labeling consequents procedure is proposed. Experimental results are presented shortly and some preliminary conclusions are made.
A genetic algorithm selection perturbative hyper-heuristic for solving ...
African Journals Online (AJOL)
The benefit of incorporating hill-climbing into operators for school timetabling is evident from previous research in this domain [3, 13, 15, 33].Versions of these ...... One of the disadvantages of hyper-heuristics is the higher runtimes as a result of having to construct a solution to evaluate each heuristic combination. This is ...
A genetic algorithm selection perturbative hyper-heuristic for solving ...
African Journals Online (AJOL)
Hyper-heuristics, on the other hand, search a heuristic space with the aim of providing a more generalized solution to the particular optimisation problem. This is a fairly new technique that has proven to be successful in solving various combinatorial optimisation problems. There has not been much research into the use of ...
Directory of Open Access Journals (Sweden)
Syed Hamid Hussain Madni
Full Text Available 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.
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.
Energy Technology Data Exchange (ETDEWEB)
Brandt, Christopher; Fieg, Georg [Hamburg University of Technology, Institute of Process and Plant Engineering, Hamburg (Germany); Luo, Xing [Helmut Schmidt University, Institute of Thermodynamics, Hamburg (Germany); University of Shanghai for Science and Technology, Institute of Thermal Engineering, Shanghai (China)
2011-08-15
In this work an innovative method for heat exchanger network (HEN) synthesis is introduced and examined. It combines a genetic algorithm (GA) with a heuristic based optimization procedure. The novel algorithm removes appearing heat load loops from the HEN structures when profitable, throughout the evolution. Two examples were examined with the new HEN synthesis method and for both better results were obtained. Thus, a positive effect of heuristic based optimization methods on the HEN synthesis with GA could be located. (orig.)
Conceptual space systems design using meta-heuristic algorithms
Kim, Byoungsoo
criteria. Two meta-heuristic optimization algorithms, Genetic Algorithms (GAs) and Simulated Annealing (SA), were used to optimize the formulated (simply bounded) Constrained Combinatorial Conceptual Space Systems Design Model. GAs and SA were demonstrated on the SAMPEX (Solar Anomalous & Magnetospheric Particle Explorer) Space System. The Conceptual Space Systems Design Model developed in this thesis can be used as an assessment tool to evaluate and validate Space System proposals.
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 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
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...... 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...
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.
Performance Study and Dynamic Optimization Design for Thread Pool Systems
Energy Technology Data Exchange (ETDEWEB)
Xu, Dongping [Iowa State Univ., Ames, IA (United States)
2004-12-19
Thread pools have been widely used by many multithreaded applications. However, the determination of the pool size according to the application behavior still remains problematic. To automate this process, in this thesis we have developed a set of performance metrics for quantitatively analyzing thread pool performance. For our experiments, we built a thread pool system which provides a general framework for thread pool research. Based on this simulation environment, we studied the performance impact brought by the thread pool on different multithreaded applications. Additionally, the correlations between internal characterizations of thread pools and their throughput were also examined. We then proposed and evaluated a heuristic algorithm to dynamically determine the optimal thread pool size. The simulation results show that this approach is effective in improving overall application performance.
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.
Greedy heuristic algorithm for solving series of eee components classification problems*
Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.
2016-04-01
Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.
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Washington Alves de Oliveira
Full Text Available ABSTRACT In this work we propose a heuristic algorithm for the layout optimization for disks installed in a rotating circular container. This is a unequal circle packing problem with additional balance constraints. It proved to be an NP-hard problem, which justifies heuristics methods for its resolution in larger instances. The main feature of our heuristic is based on the selection of the next circle to be placed inside the container according to the position of the system's center of mass. Our approach has been tested on a series of instances up to 55 circles and compared with the literature. Computational results show good performance in terms of solution quality and computational time for the proposed algorithm.
Efficient heuristic algorithm used for optimal capacitor placement in distribution systems
Energy Technology Data Exchange (ETDEWEB)
Segura, Silvio; Rider, Marcos J. [Department of Electric Energy Systems, University of Campinas, Campinas, Sao Paulo (Brazil); Romero, Ruben [Faculty of Engineering of Ilha Solteira, Paulista State University, Ilha Solteira, Sao Paulo (Brazil)
2010-01-15
An efficient heuristic algorithm is presented in this work in order to solve the optimal capacitor placement problem in radial distribution systems. The proposal uses the solution from the mathematical model after relaxing the integrality of the discrete variables as a strategy to identify the most attractive bus to add capacitors to each step of the heuristic algorithm. The relaxed mathematical model is a non-linear programming problem and is solved using a specialized interior point method. The algorithm still incorporates an additional strategy of local search that enables the finding of a group of quality solutions after small alterations in the optimization strategy. Proposed solution methodology has been implemented and tested in known electric systems getting a satisfactory outcome compared with metaheuristic methods. The tests carried out in electric systems known in specialized literature reveal the satisfactory outcome of the proposed algorithm compared with metaheuristic methods. (author)
Zheng, Jun-Xi; Zhang, Ping; Li, Fang; Du, Guang-Long
2016-09-01
Although the sequence-dependent setup times flowshop problem with the total weighted tardiness minimization objective exists widely in industry, work on the problem has been scant in the existing literature. To the authors' best knowledge, the NEH?EWDD heuristic and the Iterated Greedy (IG) algorithm with descent local search have been regarded as the high performing heuristic and the state-of-the-art algorithm for the problem, which are both based on insertion search. In this article firstly, an efficient backtracking algorithm and a novel heuristic (HPIS) are presented for insertion search. Accordingly, two heuristics are introduced, one is NEH?EWDD with HPIS for insertion search, and the other is the combination of NEH?EWDD and both the two methods. Furthermore, the authors improve the IG algorithm with the proposed methods. Finally, experimental results show that both the proposed heuristics and the improved IG (IG*) significantly outperform the original ones.
Akhmedova, Sh; Semenkin, E.
2017-02-01
Previously, a meta-heuristic approach, called Co-Operation of Biology-Related Algorithms or COBRA, for solving real-parameter optimization problems was introduced and described. COBRA’s basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, the Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm, which were chosen due to the similarity of their schemes. The performance of this meta-heuristic was evaluated on a set of test functions and its workability was demonstrated. Thus it was established that the idea of the algorithms’ cooperative work is useful. However, it is unclear which bionic algorithms should be included in this cooperation and how many of them. Therefore, the five above-listed algorithms and additionally the Fish School Search algorithm were used for the development of five different modifications of COBRA by varying the number of component-algorithms. These modifications were tested on the same set of functions and the best of them was found. Ways of further improving the COBRA algorithm are then discussed.
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.
A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows
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Chenghua Shi
2016-01-01
Full Text Available We present the vehicle routing problem with potential demands and time windows (VRP-PDTW, which is a variation of the classical VRP. A homogenous fleet of vehicles originated in a central depot serves customers with soft time windows and deliveries from/to their locations, and split delivery is considered. Also, besides the initial demand in the order contract, the potential demand caused by conformity consuming behavior is also integrated and modeled in our problem. The objective of minimizing the cost traveled by the vehicles and penalized cost due to violating time windows is then constructed. We propose a heuristics-based parthenogenetic algorithm (HPGA for successfully solving optimal solutions to the problem, in which heuristics is introduced to generate the initial solution. Computational experiments are reported for instances and the proposed algorithm is compared with genetic algorithm (GA and heuristics-based genetic algorithm (HGA from the literature. The comparison results show that our algorithm is quite competitive by considering the quality of solutions and computation time.
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.
Cheng, Jade Yu; Mailund, Thomas
2015-08-01
With full genome data from several closely related species now readily available, we have the ultimate data for demographic inference. Exploiting these full genomes, however, requires models that can explicitly model recombination along alignments of full chromosomal length. Over the last decade a class of models, based on the sequential Markov coalescence model combined with hidden Markov models, has been developed and used to make inference in simple demographic scenarios. To move forward to more complex demographic modelling we need better and more automated ways of specifying these models and efficient optimisation algorithms for inferring the parameters in complex and often high-dimensional models. In this paper we present a framework for building such coalescence hidden Markov models for pairwise alignments and present results for using heuristic optimisation algorithms for parameter estimation. We show that we can build more complex demographic models than our previous frameworks and that we obtain more accurate parameter estimates using heuristic optimisation algorithms than when using our previous gradient based approaches. Our new framework provides a flexible way of constructing coalescence hidden Markov models almost automatically. While estimating parameters in more complex models is still challenging we show that using heuristic optimisation algorithms we still get a fairly good accuracy. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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.
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.
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Sana Jawarneh
Full Text Available This paper presents a bee colony optimisation (BCO algorithm to tackle the vehicle routing problem with time window (VRPTW. The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon's 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results.
Jawarneh, Sana; Abdullah, Salwani
2015-01-01
This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon’s 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results. PMID:26132158
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.
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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.
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.
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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 Heuristic Optimal Discrete Bit Allocation Algorithm for Margin Maximization in DMT Systems
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Dong Shi-Wei
2007-01-01
Full Text Available A heuristic optimal discrete bit allocation algorithm is proposed for solving the margin maximization problem in discrete multitone (DMT systems. Starting from an initial equal power assignment bit distribution, the proposed algorithm employs a multistaged bit rate allocation scheme to meet the target rate. If the total bit rate is far from the target rate, a multiple-bits loading procedure is used to obtain a bit allocation close to the target rate. When close to the target rate, a parallel bit-loading procedure is used to achieve the target rate and this is computationally more efficient than conventional greedy bit-loading algorithm. Finally, the target bit rate distribution is checked, if it is efficient, then it is also the optimal solution; else, optimal bit distribution can be obtained only by few bit swaps. Simulation results using the standard asymmetric digital subscriber line (ADSL test loops show that the proposed algorithm is efficient for practical DMT transmissions.
Heuristic algorithm for planning and scheduling of forged pieces heat treatment
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R. Lenort
2012-04-01
Full Text Available The paper presents a heuristic algorithm for planning and scheduling of forged pieces heat treatment which allows maximizing the capacity exploitation of the heat treatment process and the entire forging process. Five Focusing Steps continuous improvement process was selected as a methodological basis for the algorithm design. Its application was supported by simulation experiments performed on a dynamic computer model of the researched process. The experimental work has made it possible to elicit the general rules for planning and scheduling of the heat treatment process of forged pieces which reduce losses caused by equipment conversion and setup times, and which increase the throughput of this process. The HIPO diagram was used to design the algorithm.
Robot navigation in unknown terrains: Introductory survey of non-heuristic algorithms
Energy Technology Data Exchange (ETDEWEB)
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 set-covering based heuristic algorithm for the periodic vehicle routing problem.
Cacchiani, V; Hemmelmayr, V C; Tricoire, F
2014-01-30
We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems.
A heuristic re-mapping algorithm reducing inter-level communication in SAMR applications.
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Steensland, Johan; Ray, Jaideep
2003-07-01
This paper aims at decreasing execution time for large-scale structured adaptive mesh refinement (SAMR) applications by proposing a new heuristic re-mapping algorithm and experimentally showing its effectiveness in reducing inter-level communication. Tests were done for five different SAMR applications. The overall goal is to engineer a dynamically adaptive meta-partitioner capable of selecting and configuring the most appropriate partitioning strategy at run-time based on current system and application state. Such a metapartitioner can significantly reduce execution times for general SAMR applications. Computer simulations of physical phenomena are becoming increasingly popular as they constitute an important complement to real-life testing. In many cases, such simulations are based on solving partial differential equations by numerical methods. Adaptive methods are crucial to efficiently utilize computer resources such as memory and CPU. But even with adaption, the simulations are computationally demanding and yield huge data sets. Thus parallelization and the efficient partitioning of data become issues of utmost importance. Adaption causes the workload to change dynamically, calling for dynamic (re-) partitioning to maintain efficient resource utilization. The proposed heuristic algorithm reduced inter-level communication substantially. Since the complexity of the proposed algorithm is low, this decrease comes at a relatively low cost. As a consequence, we draw the conclusion that the proposed re-mapping algorithm would be useful to lower overall execution times for many large SAMR applications. Due to its usefulness and its parameterization, the proposed algorithm would constitute a natural and important component of the meta-partitioner.
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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.
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Thang Trung Nguyen
2016-01-01
Full Text Available This paper proposes an efficient Cuckoo-Inspired Meta-Heuristic Algorithm (CIMHA for solving multi-objective short-term hydrothermal scheduling (ST-HTS problem. The objective is to simultaneously minimize the total cost and emission of thermal units while all constraints such as power balance, water discharge, and generation limitations must be satisfied. The proposed CIMHA is a newly developed meta-heuristic algorithm inspired by the intelligent reproduction strategy of the cuckoo bird. It is efficient for solving optimization problems with complicated objective and constraints because the method has few control parameters. The proposed method has been tested on different systems with various numbers of objective functions, and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is more efficient than many other methods for the test systems in terms of total cost, total emission, and computational time. Therefore, the proposed CIMHA can be a favorable method for solving the multi-objective ST-HTS problems.
Heuristic algorithms and a spatial decision support system for locating hydrogen-refueling stations
Lim, Seow
The vision of using hydrogen energy to replace fossil fuels as the primary energy carrier for our transportation infrastructure has been gaining recognition in recent years. The obstacles facing the hydrogen economy vision are technological feasibilities and the cost of infrastructure buildup. Technological feasibilities include the production, storage, distribution, and refueling of hydrogen energy in a safe and economical manner. The cost of infrastructure development includes the building of production plants, storage facilities, distribution network, and refueling stations of hydrogen energy. The purpose of the research is to develop heuristic algorithms and a spatial decision support system (SDSS) to facilitate efficient planning of the refueling infrastructure of hydrogen energy. Facility location-allocation models, specifically the Flow Refueling Location Model (FRLM), have been applied to determine the combination of refueling stations to be built in order to maximize the flow covered with a fixed investment cost. A mixed-integer programming version of the model has been formulated and published. While the mixed-integer programming model could be used to obtain an optimal solution for a problem, it is slow and inefficient in solving problems with a large network and large number of candidate facilities. In this research, heuristics algorithms, specifically the greedy adding, greedy adding with substitution, and genetic algorithm, are developed and applied to solve the FRLM problem. These algorithms are shown to be effective and efficient in solving complex FRLM-problems. The SDSS presented in this research integrates geographical information systems (GIS) and heuristic search algorithms to provide a flexible and powerful system for selecting the locations of hydrogen refueling stations in a real-world scenario. GIS is used to gather and process the input for the model, such as the candidate facilities and traffic flows. The SDSS also uses GIS to display and
An adaptive heuristic cross-entropy algorithm for optimal design of water distribution systems
Perelman, Lina; Ostfeld, Avi
2007-06-01
The optimal design problem of a water distribution system is to find the water distribution system component characteristics (e.g. pipe diameters, pump heads and maximum power, reservoir storage volumes, etc.) which minimize the system's capital and operational costs such that the system hydraulic laws are maintained (i.e. Kirchhoff's first and second laws), and constraints on quantities and pressures at the consumer nodes are fulfilled. In this study, an adaptive stochastic algorithm for water distribution systems optimal design based on the heuristic cross-entropy method for combinatorial optimization is presented. The algorithm is demonstrated using two well-known benchmark examples from the water distribution systems research literature for single loading gravitational systems, and an example of multiple loadings, pumping, and storage. The results show the cross-entropy dominance over previously published methods.
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.
A Hybrid Heuristic Algorithm for Ship Block Construction Space Scheduling Problem
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Shicheng Hu
2015-01-01
Full Text Available Ship block construction space is an important bottleneck resource in the process of shipbuilding, so the production scheduling optimization is a key technology to improve the efficiency of shipbuilding. With respect to ship block construction space scheduling problem, a hybrid heuristic algorithm is proposed in this paper. Firstly, Bottom-Left-Fill (BLF process is introduced. Next, an initial solution is obtained by guiding the sorting process with corners. Then on the basis of the initial solution, the simulated annealing arithmetic (SA is used to improve the solution by offering a possibility to accept worse neighbor solutions in order to escape from local optimum. Finally, the simulation experiments are conducted to verify the effectiveness of the algorithm.
Transport Logistics Optimization Model Of Passenger Car Based On Heuristic Algorithm
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Zhou Juan
2016-01-01
Full Text Available Passenger car logistics transportation problem is at the primary stage of development in China, great economic loss and waste of resources caused in the process of logistics transportation, because most of enterprises in China rely on artificial experience for guidance at present. And use of a particular genetic algorithm to solve this problem by previous also exist many defects, such as programming complexity, instability and low efficiency etc. In view of this, The heuristic algorithm designing based on the greedy thought and the 0-1 knapsack thought was proposd, according build a universal model of the logistics transportation to the passenger car.Experimental results show, this model not only recording the concrete scheme of loading,also can make the optimization by changing the loading sequence. etc. This model is applicable to solve similar problems of transport logistics, and containing great practical application value and economic value.
Optimal and heuristic algorithms of planning of low-rise residential buildings
Kartak, V. M.; Marchenko, A. A.; Petunin, A. A.; Sesekin, A. N.; Fabarisova, A. I.
2017-10-01
The problem of the optimal layout of low-rise residential building is considered. Each apartment must be no less than the corresponding apartment from the proposed list. Also all requests must be made and excess of the total square over of the total square of apartment from the list must be minimized. The difference in the squares formed due to with the discreteness of distances between bearing walls and a number of other technological limitations. It shown, that this problem is NP-hard. The authors built a linear-integer model and conducted her qualitative analysis. As well, authors developed a heuristic algorithm for the solution tasks of a high dimension. The computational experiment was conducted which confirming the efficiency of the proposed approach. Practical recommendations on the use the proposed algorithms are given.
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Haitham El-Hussieny
2015-04-01
Full Text Available Mobile robots have been used to explore novel environments and build useful maps for navigation. Although sensor-based random tree techniques have been used extensively for exploration, they are not efficient for time-critical applications since the robot may visit the same place more than once during backtracking. In this paper, a novel, simple yet effective heuristic backtracking algorithm is proposed to reduce the exploration time and distance travelled. The new algorithm is based on the selection of the most informative node to approach during backtracking. A new environmental complexity metric is developed to evaluate the exploration complexity of different structured environments and thus enable a fair comparison between exploration techniques. An evaluation index is also developed to encapsulate the total performance of an exploration technique in a single number for the comparison of techniques. The developed backtracking algorithm is tested through computer simulations for several structured environments to verify its effectiveness using the developed complexity metric and the evaluation index. The results confirmed significant performance improvement using the proposed algorithm. The new evaluation index is also shown to be representative of the performance and to facilitate comparisons.
A heuristic algorithm based on tabu search for vehicle routing problems with backhauls
Directory of Open Access Journals (Sweden)
Jhon Jairo Santa Chávez
2017-07-01
Full Text Available In this paper, a heuristic algorithm based on Tabu Search Approach for solving the Vehicle Routing Problem with Backhauls (VRPB is proposed. The problem considers a set of customers divided in two subsets: Linehaul and Backhaul customers. Each Linehaul customer requires the delivery of a given quantity of product from the depot, whereas a given quantity of product must be picked up from each Backhaul customer and transported to the depot. In the proposed algorithm, each route consists of one sub-route in which only the delivery task is done, and one sub-route in which only the collection process is performed. The search process allows obtaining a correct order to visit all the customers on each sub-route. In addition, the proposed algorithm determines the best connections among the sub-routes in order to obtain a global solution with the minimum traveling cost. The efficiency of the algorithm is evaluated on a set of benchmark instances taken from the literature. The results show that the computing times are greatly reduced with a high quality of solutions. Finally, conclusions and suggestions for future works are presented.
A Multi-Inner-World Genetic Algorithm Using Multiple Heuristics to Optimize Delivery Schedule
Sakurai, Yoshitaka; Onoyama, Takashi; Tsukamoto, Natsuki; Takada, Kouhei; Tsuruta, Setsuo
A delivery route optimization that improves the efficiency of real time delivery or a distribution network requires to solve several tens to hundreds cities Traveling Salesman Problems (TSP) (1)(2) within interactive response time, with expert-level accuracy (less than about 3% of error rate). To meet these requirements, a multi-inner-world Genetic Algorithm (Miw-GA) method is developed. This method combines several types of GA's inner worlds. Each world of this method uses a different type of heuristics such as a 2-opt type mutation world and a block (Nearest Insertion) type mutation world. Comparison based on the results of experiments proved the method is superior to others and our previously proposed method.
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...
Damage identification of a TLP floating wind turbine by meta-heuristic algorithms
Ettefagh, M. M.
2015-12-01
Damage identification of the offshore floating wind turbine by vibration/dynamic signals is one of the important and new research fields in the Structural Health Monitoring (SHM). In this paper a new damage identification method is proposed based on meta-heuristic algorithms using the dynamic response of the TLP (Tension-Leg Platform) floating wind turbine structure. The Genetic Algorithms (GA), Artificial Immune System (AIS), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC) are chosen for minimizing the object function, defined properly for damage identification purpose. In addition to studying the capability of mentioned algorithms in correctly identifying the damage, the effect of the response type on the results of identification is studied. Also, the results of proposed damage identification are investigated with considering possible uncertainties of the structure. Finally, for evaluating the proposed method in real condition, a 1/100 scaled experimental setup of TLP Floating Wind Turbine (TLPFWT) is provided in a laboratory scale and the proposed damage identification method is applied to the scaled turbine.
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.
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.
Index Fund Optimization Using a Genetic Algorithm and a Heuristic Local Search
Orito, Yukiko; Inoguchi, Manabu; Yamamoto, Hisashi
It is well known that index funds are popular passively managed portfolios and have been used very extensively for the hedge trading. Index funds consist of a certain number of stocks of listed companies on a stock market such that the fund's return rates follow a similar path to the changing rates of the market indices. However it is hard to make a perfect index fund consisting of all companies included in the given market index. Thus, the index fund optimization can be viewed as a combinatorial optimization for portfolio managements. In this paper, we propose an optimization method that consists of a genetic algorithm and a heuristic local search algorithm to make strong linear association between the fund's return rates and the changing rates of market index. We apply the method to the Tokyo Stock Exchange and make index funds whose return rates follow a similar path to the changing rates of Tokyo Stock Price Index (TOPIX). The results show that our proposal method makes the index funds with strong linear association to the market index by small computing time.
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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.
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.
FC-TLBO: fully constrained meta-heuristic algorithm for abundance ...
Indian Academy of Sciences (India)
Omprakash Tembhurne
noise ratio on simulated and real hyperspectral data demonstrate that the proposed ... abundance sum to one constraint (ASC); hyperspectral unmixing; meta-heuristic approach; teaching-learning-based optimisation (TLBO). 1. Introduction.
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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
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.
A New Heuristic Algorithm for Protein Folding in the HP Model.
Traykov, Metodi; Angelov, Slav; Yanev, Nicola
2016-08-01
This article presents an efficient heuristic for protein folding. The protein folding problem is to predict the compact three-dimensional structure of a protein based on its amino acid sequence. The focus is on an original integer programming model derived from a platform used for Contact Map Overlap problem.
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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.
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.
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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.
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Jian-Lin Jiang
2013-01-01
Full Text Available This paper considers the locations of multiple facilities in the space , with the aim of minimizing the sum of weighted distances between facilities and regional customers, where the proximity between a facility and a regional customer is evaluated by the closest distance. Due to the fact that facilities are usually allowed to be sited in certain restricted areas, some locational constraints are imposed to the facilities of our problem. In addition, since the symmetry of distances is sometimes violated in practical situations, the gauge is employed in this paper instead of the frequently used norms for measuring both the symmetric and asymmetric distances. In the spirit of the Cooper algorithm (Cooper, 1964, a new location-allocation heuristic algorithm is proposed to solve this problem. In the location phase, the single-source subproblem with regional demands is reformulated into an equivalent linear variational inequality (LVI, and then, a projection-contraction (PC method is adopted to find the optimal locations of facilities, whereas in the allocation phase, the regional customers are allocated to facilities according to the nearest center reclassification (NCR. The convergence of the proposed algorithm is proved under mild assumptions. Some preliminary numerical results are reported to show the effectiveness of the new algorithm.
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.
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Hui Zhou
2016-10-01
Full Text Available 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.
Wu, Hao; Wan, Zhong
2018-02-01
In this paper, a multiobjective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning, and adjustment of production capacity. Different from the existing approaches, the social negative effect, generated from structural optimization of the recycling system, is minimized in our model, as well as the total recycling profit and utility from environmental improvement are jointly maximized. For solving the problem, the MOMIPNLP model is first transformed into an ordinary mixed-integer nonlinear programming model by variable substitution such that the piecewise feature of the model is removed. Then, based on technique of orthogonal design, a hybrid heuristic algorithm is developed to find an approximate Pareto-optimal solution, where genetic algorithm is used to optimize the structure of search neighborhood, and both local branching algorithm and relaxation-induced neighborhood search algorithm are employed to cut the searching branches and reduce the number of variables in each branch. Numerical experiments indicate that this algorithm spends less CPU (central processing unit) time in solving large-scale regional urban mining management problems, especially in comparison with the similar ones available in literature. By case study and sensitivity analysis, a number of practical managerial implications are revealed from the model. Since the metal stocks in society are reliable overground mineral sources, urban mining has been paid great attention as emerging strategic resources in an era of resource shortage. By mathematical modeling and development of efficient algorithms, this paper provides decision makers with useful suggestions on the optimal design of recycling system in urban mining. For example, this paper can answer how to encourage enterprises to join the recycling activities
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...
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.
Luis, Martino; Ramli, Mohammad Fadzli; Lin, Abdullah
2016-10-01
This study investigates the capacitated planar multi-facility location-allocation problem by considering various capacity constraints. The problem is also known as the capacitated multi-source Weber problem, where the number of facilities to be located is specified and each of which has a capacity constraint. An efficient greedy randomised adaptive search procedure (GRASP) is proposed to deal with the problem. A scheme that applies the furthest distance rule (FDR) and self-adjusted threshold parameters to generate initial facility locations that are situated sparsely within GRASP framework is also presented. The construction of the restricted candidate list (RCL) within GRASP is also guided by applying a concept of restricted regions that prevents new facility locations to be sited too close to the previous selected facility locations. The performance of the proposed GRASP heuristics is tested using benchmark data sets from literature. The computational experiments show that the proposed methods provide encouraging solutions when compared to recently published papers. Some future research avenues on the subject are also briefly highlighted.
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.
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.
BiCluE - Exact and heuristic algorithms for weighted bi-cluster editing of biomedical data
2013-01-01
Background The explosion of biological data has dramatically reformed today's biology research. The biggest challenge to biologists and bioinformaticians is the integration and analysis of large quantity of data to provide meaningful insights. One major problem is the combined analysis of data from different types. Bi-cluster editing, as a special case of clustering, which partitions two different types of data simultaneously, might be used for several biomedical scenarios. However, the underlying algorithmic problem is NP-hard. Results Here we contribute with BiCluE, a software package designed 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 applied our implementation on real world biomedical data, GWAS data in this case. BiCluE generally works on any kind of data types that can be modeled as (weighted or unweighted) bipartite graphs. Conclusions To our knowledge, this is the first software package solving the weighted bi-cluster editing problem. BiCluE as well as the supplementary results are available online at http://biclue.mpi-inf.mpg.de. PMID:24565035
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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.
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.
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)
Heuristic algorithms for a storage location assignment problem in a chaotic warehouse
Quintanilla, Sacramento; Pérez, Ángeles; Ballestín, Francisco; Lino, Pilar
2015-10-01
The extensive application of emerging technologies is revolutionizing warehouse management. These technologies facilitate working with complex and powerful warehouse management models in which products do not have assigned fixed locations (random storage). Random storage allows the utilization of the available space to be optimized. In this context, and motivated by a real problem, this article presents a model that looks for the optimal allocation of goods in order to maximize the storage space availability within the restrictions of the warehouse. For the proposed model a construction method, a local search algorithm and different metaheuristics have been developed. The introduced algorithms can also be used for other purposes such as to assess when and how it is convenient to perform relocation of stored items to improve the current level of storage space availability. Computational tests performed on a set of randomly generated and real warehouse instances show the effectiveness of the proposed methods.
Solving the vehicle routing problem by a hybrid meta-heuristic algorithm
Yousefikhoshbakht, Majid; Khorram, Esmaile
2012-08-01
The vehicle routing problem (VRP) is one of the most important combinational optimization problems that has nowadays received much attention because of its real application in industrial and service problems. The VRP involves routing a fleet of vehicles, each of them visiting a set of nodes such that every node is visited by exactly one vehicle only once. So, the objective is to minimize the total distance traveled by all the vehicles. This paper presents a hybrid two-phase algorithm called sweep algorithm (SW) + ant colony system (ACS) for the classical VRP. At the first stage, the VRP is solved by the SW, and at the second stage, the ACS and 3-opt local search are used for improving the solutions. Extensive computational tests on standard instances from the literature confirm the effectiveness of the presented approach.
Harmonic Optimization in Voltage Source Inverter for PV Application using Heuristic Algorithms
Kandil, Shaimaa A.; Ali, A. A.; El Samahy, Adel; Wasfi, Sherif M.; Malik, O. P.
2016-12-01
Selective Harmonic Elimination (SHE) technique is the fundamental switching frequency scheme that is used to eliminate specific order harmonics. Its application to minimize low order harmonics in a three level inverter is proposed in this paper. The modulation strategy used here is SHEPWM and the nonlinear equations, that characterize the low order harmonics, are solved using Harmony Search Algorithm (HSA) to obtain the optimal switching angles that minimize the required harmonics and maintain the fundamental at the desired value. Total Harmonic Distortion (THD) of the output voltage is minimized maintaining selected harmonics within allowable limits. A comparison has been drawn between HSA, Genetic Algorithm (GA) and Newton Raphson (NR) technique using MATLAB software to determine the effectiveness of getting optimized switching angles.
Directory of Open Access Journals (Sweden)
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.
Energy Technology Data Exchange (ETDEWEB)
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.
De Masi, Elen C D J; De Masi, Flávia D J; De Masi, Roberta D J
2016-12-01
Suture threads are a minimally invasive surgical technique for facial rejuvenation. Its use was initiated by Sulamanidze et al with propylene after Serdev introduced suture with polycaproamide; however, these types of suture increased inflammatory reaction. For correction of the aging face, surgeons are devising more procedures with fewer incisions and shorter postoperative recovery periods. Many of these procedures use absorbable and nonabsorbable sutures in the dermis and subcutis to lift lax skin. The polydioxanone suture is currently a great option for antiaging treatment, because besides the ease of applicability and good results, it also has a low incidence of adverse reactions. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
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.
A Multi-Threading Algorithm to Detect and Remove Cycles in Vertex- and Arc-Weighted Digraph
Directory of Open Access Journals (Sweden)
Huanqing Cui
2017-10-01
Full Text Available A graph is a very important structure to describe many applications in the real world. In many applications, such as dependency graphs and debt graphs, it is an important problem to find and remove cycles to make these graphs be cycle-free. The common algorithm often leads to an out-of-memory exception in commodity personal computer, and it cannot leverage the advantage of multicore computers. This paper introduces a new problem, cycle detection and removal with vertex priority. It proposes a multithreading iterative algorithm to solve this problem for large-scale graphs on personal computers. The algorithm includes three main steps: simplification to decrease the scale of graph, calculation of strongly connected components, and cycle detection and removal according to a pre-defined priority in parallel. This algorithm avoids the out-of-memory exception by simplification and iteration, and it leverages the advantage of multicore computers by multithreading parallelism. Five different versions of the proposed algorithm are compared by experiments, and the results show that the parallel iterative algorithm outperforms the others, and simplification can effectively improve the algorithm's performance.
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.
Mignon, David; Simonson, Thomas
2016-07-15
Computational protein design depends on an energy function and an algorithm to search the sequence/conformation space. We compare three stochastic search algorithms: a heuristic, Monte Carlo (MC), and a Replica Exchange Monte Carlo method (REMC). The heuristic performs a steepest-descent minimization starting from thousands of random starting points. The methods are applied to nine test proteins from three structural families, with a fixed backbone structure, a molecular mechanics energy function, and with 1, 5, 10, 20, 30, or all amino acids allowed to mutate. Results are compared to an exact, "Cost Function Network" method that identifies the global minimum energy conformation (GMEC) in favorable cases. The designed sequences accurately reproduce experimental sequences in the hydrophobic core. The heuristic and REMC agree closely and reproduce the GMEC when it is known, with a few exceptions. Plain MC performs well for most cases, occasionally departing from the GMEC by 3-4 kcal/mol. With REMC, the diversity of the sequences sampled agrees with exact enumeration where the latter is possible: up to 2 kcal/mol above the GMEC. Beyond, room temperature replicas sample sequences up to 10 kcal/mol above the GMEC, providing thermal averages and a solution to the inverse protein folding problem. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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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.
Srinivas, B; Kulick, S N; Doran, Christine; Kulick, Seth
1995-01-01
There are currently two philosophies for building grammars and parsers -- Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.
Albuquerque, Fabio; Beier, Paul
2015-01-01
Here we report that prioritizing sites in order of rarity-weighted richness (RWR) is a simple, reliable way to identify sites that represent all species in the fewest number of sites (minimum set problem) or to identify sites that represent the largest number of species within a given number of sites (maximum coverage problem). We compared the number of species represented in sites prioritized by RWR to numbers of species represented in sites prioritized by the Zonation software package for 11 datasets in which the size of individual planning units (sites) ranged from <1 ha to 2,500 km2. On average, RWR solutions were more efficient than Zonation solutions. Integer programming remains the only guaranteed way find an optimal solution, and heuristic algorithms remain superior for conservation prioritizations that consider compactness and multiple near-optimal solutions in addition to species representation. But because RWR can be implemented easily and quickly in R or a spreadsheet, it is an attractive alternative to integer programming or heuristic algorithms in some conservation prioritization contexts.
A new heuristic for the quadratic assignment problem
Zvi Drezner
2002-01-01
We propose a new heuristic for the solution of the quadratic assignment problem. The heuristic combines ideas from tabu search and genetic algorithms. Run times are very short compared with other heuristic procedures. The heuristic performed very well on a set of test problems.
Sunstein, Cass R
2005-08-01
With respect to questions of fact, people use heuristics--mental short-cuts, or rules of thumb, that generally work well, but that also lead to systematic errors. People use moral heuristics too--moral short-cuts, or rules of thumb, that lead to mistaken and even absurd moral judgments. These judgments are highly relevant not only to morality, but to law and politics as well. examples are given from a number of domains, including risk regulation, punishment, reproduction and sexuality, and the act/omission distinction. in all of these contexts, rapid, intuitive judgments make a great deal of sense, but sometimes produce moral mistakes that are replicated in law and policy. One implication is that moral assessments ought not to be made by appealing to intuitions about exotic cases and problems; those intuitions are particularly unlikely to be reliable. Another implication is that some deeply held moral judgments are unsound if they are products of moral heuristics. The idea of error-prone heuristics is especially controversial in the moral domain, where agreement on the correct answer may be hard to elicit; but in many contexts, heuristics are at work and they do real damage. Moral framing effects, including those in the context of obligations to future generations, are also discussed.
Dawid Połap; Marcin Woz´niak
2017-01-01
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 mat...
Bolt Thread Stress Optimization
DEFF Research Database (Denmark)
Pedersen, Niels Leergaard
2012-01-01
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 this paper. Thread root design controls the stress concentration factor...... 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...
Directory of Open Access Journals (Sweden)
Dania Tamayo-Vera
2016-04-01
Full Text Available Spanish abstract Los problemas lineales con restricciones de equilibrio son un caso particular de los modelos de optimización con restricciones de equilibrio. Debido a la complejidad que presentan, la condición de equilibrio se sustituye por condiciones necesarias obteniéndose un problema con restricciones de complementariedad (MPCC. La estructura del conjunto de soluciones factibles del MPCC obtenido es compleja ya que es la unión de poliedros. Resolver todos los problemas correspondientes a minimizar la función objetivo sobre cada uno de estos poliedros es computacionalmente costoso. El presente trabajo utiliza un enfoque heurístico para dar solución al MPCC, adaptando los algoritmos de Búsqueda Local y Recocido Simulado. Este trabajo presenta un conjunto de funciones de prueba y los resultados computacionales más significativos obtenidos. English abstract Linear equilibrium constrained programming is a special class of optimization models with equilibrium constraints. Because of the complexity of the equilibrium condition it is replaced by necessary conditions, which leads to a complementarity constrained problem (MPCC. The set of feasible solutions in a MPCC is structured as a union of polyhedrons. Solving the MPCC problem would require the minimization of the objective function on each of these polyhedrons. The computation cost of this approach is unfeasible, thus, this work presents a new approach where heuristic algorithms such as Hill Climbing and Simulated Annealing are used to search for good solutions on the polyhedrons space. A new benchmark for linear equilibrium constrained optimization is introduced. The computational results achieved by the proposed heuristics on the new benchmark are presented.
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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.
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Gordana Radivojević
2006-10-01
Full Text Available Transportni sistem "Nazovi vožnju" (Dial-a-Ride oblik je prevoza u kojem prevozilac poseduje vozni park i realizuje prevoz na relacijama i u vreme kako to zahtevaju korisnici. Osnovni problem organizatora prevoza je definisanje ruta i reda vožnje saobraćajnih sredstava, tako da se realizuje skup zahteva za prevoz. U radu je opisan heuristički algoritam za projektovanje ruta i redova vožnje saobraćajnih sredstava za statički slučaj transportnog sistema "Nazovi vožnju". Razvijeni heuristički algoritam ima mogućnost primene u konkretnim uslovima. / Dial-a-Ride system is a way of transport in which a transporter owns a fleet and realizes transport when and where customers ask for it. Different versions of this type of transportation are present in every day practice. The main problem here is route design and scheduling to realize the set of transport requests. In this paper it is described a heuristic algorithm for route design and scheduling for the static Dial-a-Ride problem. The developed algorithm can be applied in real situations.
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.
Investigations of quantum heuristics for optimization
Rieffel, Eleanor; Hadfield, Stuart; Jiang, Zhang; Mandra, Salvatore; Venturelli, Davide; Wang, Zhihui
We explore the design of quantum heuristics for optimization, focusing on the quantum approximate optimization algorithm, a metaheuristic developed by Farhi, Goldstone, and Gutmann. We develop specific instantiations of the of quantum approximate optimization algorithm for a variety of challenging combinatorial optimization problems. Through theoretical analyses and numeric investigations of select problems, we provide insight into parameter setting and Hamiltonian design for quantum approximate optimization algorithms and related quantum heuristics, and into their implementation on hardware realizable in the near term.
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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.
Ryzhikov, I. S.; Semenkin, E. S.
2017-02-01
This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.
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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.
Model of Wagons’ Placing-In and Taking-Out Problem in a Railway Station and Its Heuristic Algorithm
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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.
A Heuristic Approach to Scheduling University Timetables.
Loo, E. H.; And Others
1986-01-01
Categories of facilities utilization and scheduling requirements to be considered when using a heuristic approach to timetabling are described together with a nine-step algorithm and the computerized timetabling system, Timetable Schedules System (TTS); TTS utilizes heuristic approach. An example demonstrating use of TTS and a program flowchart…
Redd, Andrew M; Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Tran, Le-Thuy; Samore, Matthew H
2017-07-01
Templates in text notes pose challenges for automated information extraction algorithms. We propose a method that identifies novel templates in plain text medical notes. The identification can then be used to either include or exclude templates when processing notes for information extraction. The two-module method is based on the framework of information foraging and addresses the hypothesis that documents containing templates and the templates within those documents can be identified by common features. The first module takes documents from the corpus and groups those with common templates. This is accomplished through a binned word count hierarchical clustering algorithm. The second module extracts the templates. It uses the groupings and performs a longest common subsequence (LCS) algorithm to obtain the constituent parts of the templates. The method was developed and tested on a random document corpus of 750 notes derived from a large database of US Department of Veterans Affairs (VA) electronic medical notes. The grouping module, using hierarchical clustering, identified 23 groups with 3 documents or more, consisting of 120 documents from the 750 documents in our test corpus. Of these, 18 groups had at least one common template that was present in all documents in the group for a positive predictive value of 78%. The LCS extraction module performed with 100% positive predictive value, 94% sensitivity, and 83% negative predictive value. The human review determined that in 4 groups the template covered the entire document, with the remaining 14 groups containing a common section template. Among documents with templates, the number of templates per document ranged from 1 to 14. The mean and median number of templates per group was 5.9 and 5, respectively. The grouping method was successful in finding like documents containing templates. Of the groups of documents containing templates, the LCS module was successful in deciphering text belonging to the template
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.
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.
Critical Path-Based Thread Placement for NUMA Systems
Energy Technology Data Exchange (ETDEWEB)
Su, C Y; Li, D; Nikolopoulos, D S; Grove, M; Cameron, K; de Supinski, B R
2011-11-01
Multicore multiprocessors use a Non Uniform Memory Architecture (NUMA) to improve their scalability. However, NUMA introduces performance penalties due to remote memory accesses. Without efficiently managing data layout and thread mapping to cores, scientific applications, even if they are optimized for NUMA, may suffer performance loss. In this paper, we present algorithms and a runtime system that optimize the execution of OpenMP applications on NUMA architectures. By collecting information from hardware counters, the runtime system directs thread placement and reduces performance penalties by minimizing the critical path of OpenMP parallel regions. The runtime system uses a scalable algorithm that derives placement decisions with negligible overhead. We evaluate our algorithms and runtime system with four NPB applications implemented in OpenMP. On average the algorithms achieve between 8.13% and 25.68% performance improvement compared to the default Linux thread placement scheme. The algorithms miss the optimal thread placement in only 8.9% of the cases.
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.
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.
Heuristic methods for shared backup path protection planning
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin
2012-01-01
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
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...
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.
Deterministic oscillatory search: a new meta-heuristic optimization ...
Indian Academy of Sciences (India)
heuristic optimization; power system problem. Abstract. The paper proposes a new optimization algorithm that is extremely robust in solving mathematical and engineering problems. The algorithm combines the deterministic nature of classical ...
Topical perspective on massive threading and parallelism.
Farber, Robert M
2011-09-01
Unquestionably computer architectures have undergone a recent and noteworthy paradigm shift that now delivers multi- and many-core systems with tens to many thousands of concurrent hardware processing elements per workstation or supercomputer node. GPGPU (General Purpose Graphics Processor Unit) technology in particular has attracted significant attention as new software development capabilities, namely CUDA (Compute Unified Device Architecture) and OpenCL™, have made it possible for students as well as small and large research organizations to achieve excellent speedup for many applications over more conventional computing architectures. The current scientific literature reflects this shift with numerous examples of GPGPU applications that have achieved one, two, and in some special cases, three-orders of magnitude increased computational performance through the use of massive threading to exploit parallelism. Multi-core architectures are also evolving quickly to exploit both massive-threading and massive-parallelism such as the 1.3 million threads Blue Waters supercomputer. The challenge confronting scientists in planning future experimental and theoretical research efforts--be they individual efforts with one computer or collaborative efforts proposing to use the largest supercomputers in the world is how to capitalize on these new massively threaded computational architectures--especially as not all computational problems will scale to massive parallelism. In particular, the costs associated with restructuring software (and potentially redesigning algorithms) to exploit the parallelism of these multi- and many-threaded machines must be considered along with application scalability and lifespan. This perspective is an overview of the current state of threading and parallelize with some insight into the future. Published by Elsevier Inc.
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
Directory of Open Access Journals (Sweden)
A A Eicher
2012-09-01
Full Text Available Magnetic Resonance Imaging provides a non-invasive means to study the neural correlates of Fetal Alcohol Spectrum Disorder (FASD - the most common form of preventable mental retardation worldwide. One approach aims to detect brain abnormalities through an assessment of volume and shape of two sub-cortical structures, the caudate nucleus and hippocampus. We present a method for automatically segmenting these structures from high-resolution MR images captured as part of an ongoing study into the neural correlates of FASD. Our method incorporates an Active Shape Model, which is used to learn shape variation from manually segmented training data. A modified discrete Geometrically Deformable Model is used to generate point correspondence between training models. An ASM is then created from the landmark points. Experiments were conducted on the image search phase of ASM segmentation, in order to find the technique best suited to segmentation of the hippocampus and caudate nucleus. Various popular image search techniques were tested, including an edge detection method and a method based on grey profile Mahalanobis distance measurement. A novel heuristic image search method was also developed and tested. This heuristic method improves image segmentation by taking advantage of characteristics specific to the target data, such as a relatively homogeneous tissue colour in target structures. Results show that ASMs that use the heuristic image search technique produce the most accurate segmentations. An ASM constructed using this technique will enable researchers to quickly, reliably, and automatically segment test data for use in the FASD study.
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.
Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN; Ratterman, Joseph D [Rochester, MN
2011-06-07
Methods, compute nodes, and computer program products are provided for heuristic status polling of a component in a computing system. Embodiments include receiving, by a polling module from a requesting application, a status request requesting status of a component; determining, by the polling module, whether an activity history for the component satisfies heuristic polling criteria; polling, by the polling module, the component for status if the activity history for the component satisfies the heuristic polling criteria; and not polling, by the polling module, the component for status if the activity history for the component does not satisfy the heuristic criteria.
Mohsen Mousavi, Seyed; Niaki, Seyed Taghi Akhavan; Mehdizadeh, Esmaeil; Tavarroth, Mohammad Reza
2013-10-01
A new mathematical model for the capacitated multi-facility location-allocation problem with probabilistic customers' locations and demands is developed in this article. The model is formulated into the frameworks of the expected value model (EVM) and the chance-constrained programming (CCP) based on two different distance measures. In order to solve the model, two hybrid intelligent algorithms are proposed, where the simplex algorithm and stochastic simulation are the bases for both algorithms. However, in the first algorithm, named SSGA, a special type of genetic algorithm is combined and in the second, SSVDO, a vibration-damping optimisation (VDO) algorithm is united. The Taguchi method is employed to tune the parameters of the two proposed algorithms. Finally, some numerical examples are given to illustrate the applications of the proposed methodologies and to compare their performances.
Heuristic approach to the passive optical network with fibre duct ...
African Journals Online (AJOL)
Integer programming, network flow optimisation, passive optical network, ... algorithm before providing a greedy planning heuristic [11]. The multi- ... A wide range of meta-heuristics have also been employed to solve PONPP, with genetic ... In the case of PONPP, the objective is to find a subset of open facilities F, with every.
Denotational semantics for thread algebra
Vu, T.D.
2008-01-01
This paper gives a denotational semantics for thread algebra (TA), an algebraic framework for the description and analysis of recent programming languages such as C# and Java [J.A. Bergstra, C.A. Middelburg, Thread algebra for strategic interleaving, Formal Aspects of Computing, in press.
Sanjuan-Estrada, J.F.; Casado, L.G.; García, I.; Hendrix, E.M.T.
2012-01-01
Dynamically determining the appropriate number of threads for a multi-threaded application may lead to a higher efficiency than predetermining the number of threads beforehand. Interval branch-and-bound (B&B) global optimization algorithms are typically irregular algorithms that may benefit from
DEFF Research Database (Denmark)
Sousa, Tiago; Morais, Hugo; Castro, Rui
2016-01-01
will turn the day-ahead optimal resource scheduling problem into an even more difficult optimization problem. Under these circumstances, metaheuristics can be used to address this optimization problem. An adequate algorithm for generating a good initial solution can improve the metaheuristic's performance...... of finding a final solution near to the optimal than using a random initial solution. This paper proposes two initial solution algorithms to be used by a metaheuristic technique (simulated annealing). These algorithms are tested and evaluated with other published algorithms that obtain initial solution....... The proposed algorithms have been developed as modules to be more flexible their use by other metaheuristics than just simulated annealing. The simulated annealing with different initial solution algorithms has been tested in a 37-bus distribution network with distributed resources, especially electric...
Threaded pilot insures cutting tool alignment
Goldman, R.; Schneider, W. E.
1966-01-01
Threaded pilot allows machining of a port component, or boss, after the reciprocating hole has been threaded. It is used to align cutting surfaces with the boss threads, thus insuring precision alignment.
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 and bias in homeopathy.
Souter, K
2006-10-01
The practice of Homeopathy ought to be strictly logical. In the Organon Samuel Hahnemann gives the impression that the unprejudiced observer should be able to follow an algorithmic route to the simillimum in every case. Judgement and Decision Research, however, indicates that when people grapple with complex systems like homeopathy they are more likely to use heuristics or empirical rules to help them reach a solution. Thus Hahnemann's concept of the unprejudiced observer is virtually impossible to attain. There is inevitable bias in both case-taking and remedy selection. Understanding the types of bias may enable the practitioner to reduce his/her own bias.
Heuristic framework for parallel sorting computations | Nwanze ...
African Journals Online (AJOL)
The decreasing cost of these processors will probably in the future, make the solutions that are derived thereof to be more appealing. Efficient algorithms for sorting scheme that are encountered in a number of operations are considered for multi-user machines. A heuristic framework for exploiting parallelism inherent in ...
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.
Recursive heuristic classification
Wilkins, David C.
1994-01-01
The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.
Heuristics Considering UX and Quality Criteria for Heuristics
Directory of Open Access Journals (Sweden)
Frederik Bader
2017-12-01
Full Text Available Heuristic evaluation is a cheap tool with which one can take qualitative measures of a product’s usability. However, since the methodology was first presented, the User Experience (UX has become more popular but the heuristics have remained the same. In this paper, we analyse the current state of heuristic evaluation in terms of heuristics for measuring the UX. To do so, we carried out a literature review. In addition, we had a look at different heuristics and mapped them with the UX dimensions of the User Experience Questionnaire (UEQ. Moreover, we proposed a quality model for heuristic evaluation and a list of quality criteria for heuristics.
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.
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...
Protein Structure Determination Using Protein Threading and Sparse NMR Data
Energy Technology Data Exchange (ETDEWEB)
Crawford, O.H.; Einstein, J.R.; Xu, D.; Xu, Y.
1999-11-14
It is well known that the NMR method for protein structure determination applies to small proteins and that its effectiveness decreases very rapidly as the molecular weight increases beyond about 30 kD. We have recently developed a method for protein structure determination that can fully utilize partial NMR data as calculation constraints. The core of the method is a threading algorithm that guarantees to find a globally optimal alignment between a query sequence and a template structure, under distance constraints specified by NMR/NOE data. Our preliminary tests have demonstrated that a small number of NMR/NOE distance restraints can significantly improve threading performance in both fold recognition and threading-alignment accuracy, and can possibly extend threading's scope of applicability from structural homologs to structural analogs. An accurate backbone structure generated by NMR-constrained threading can then provide a significant amount of structural information, equivalent to that provided by the NMR method with many NMR/NOE restraints; and hence can greatly reduce the amount of NMR data typically required for accurate structure determination. Our preliminary study suggests that a small number of NMR/NOE restraints may suffice to determine adequately the all-atom structure when those restraints are incorporated in a procedure combining threading, modeling of loops and sidechains, and molecular dynamics simulation. Potentially, this new technique can expand NMR's capability to larger proteins.
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…
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.
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.
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.
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
Efficient Thread Mapping for Heterogeneous Multicore IoT Systems
Directory of Open Access Journals (Sweden)
Thomas Mezmur Birhanu
2017-01-01
Full Text Available This paper proposes a thread scheduling mechanism primed for heterogeneously configured multicore systems. Our approach considers CPU utilization for mapping running threads with the appropriate core that can potentially deliver the actual needed capacity. The paper also introduces a mapping algorithm that is able to map threads to cores in an O(N log M time complexity, where N is the number of cores and M is the number of types of cores. In addition to that we also introduced a method of profiling heterogeneous architectures based on the discrepancy between the performances of individual cores. Our heterogeneity aware scheduler was able to speed up processing by 52.62% and save power by 2.22% as compared to the CFS scheduler that is a default in Linux systems.
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.
Method for molding threads in graphite panels
Short, W.W.; Spencer, C.
1994-11-29
A graphite panel with a hole having a damaged thread is repaired by drilling the hole to remove all of the thread and making a new hole of larger diameter. A bolt with a lubricated thread is placed in the new hole and the hole is packed with graphite cement to fill the hole and the thread on the bolt. The graphite cement is cured, and the bolt is unscrewed therefrom to leave a thread in the cement which is at least as strong as that of the original thread. 8 figures.
Heuristics for the inversion median problem
2010-01-01
Background The study of genome rearrangements has become a mainstay of phylogenetics and comparative genomics. Fundamental in such a study is the median problem: given three genomes find a fourth that minimizes the sum of the evolutionary distances between itself and the given three. Many exact algorithms and heuristics have been developed for the inversion median problem, of which the best known is MGR. Results We present a unifying framework for median heuristics, which enables us to clarify existing strategies and to place them in a partial ordering. Analysis of this framework leads to a new insight: the best strategies continue to refer to the input data rather than reducing the problem to smaller instances. Using this insight, we develop a new heuristic for inversion medians that uses input data to the end of its computation and leverages our previous work with DCJ medians. Finally, we present the results of extensive experimentation showing that our new heuristic outperforms all others in accuracy and, especially, in running time: the heuristic typically returns solutions within 1% of optimal and runs in seconds to minutes even on genomes with 25'000 genes--in contrast, MGR can take days on instances of 200 genes and cannot be used beyond 1'000 genes. Conclusion Finding good rearrangement medians, in particular inversion medians, had long been regarded as the computational bottleneck in whole-genome studies. Our new heuristic for inversion medians, ASM, which dominates all others in our framework, puts that issue to rest by providing near-optimal solutions within seconds to minutes on even the largest genomes. PMID:20122203
Theory of Randomized Search Heuristics in Combinatorial Optimization
DEFF Research Database (Denmark)
such as time, money, or knowledge to obtain good specific algorithms. It is widely acknowledged that a solid mathematical foundation for such heuristics is needed. Most designers of RSHs, however, rather focused on mimicking processes in nature (such as evolution) rather than making the heuristics amenable......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...... to a mathematical analysis. This is different to the classical design of (randomized) algorithms which are developed with their theoretical analysis of runtime (and proof of correctness) in mind. Despite these obstacles, research from the last about 15 years has shown how to apply the methods for the probabilistic...
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...
2015-09-01
the sewing thread were made using blends of nylon or cotton along with para-aramid and recycled para-aramid fibers. The individual yarns were then...TELEPHONE NUMBER (include area code) (508) 233-4313 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 YARNS COTTON ... Introduction ...........................................................................................................1 2. Key Objectives
Indian Academy of Sciences (India)
positive numbers. The word 'algorithm' was most often associated with this algorithm till 1950. It may however be pOinted out that several non-trivial algorithms such as synthetic (polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used.
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)
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...... would like to emphasize another side to the algorithmic everyday life. We argue that algorithms can instigate and facilitate imagination, creativity, and frivolity, while saying something that is simultaneously old and new, always almost repeating what was before but never quite returning. We show...... this by threading together stimulating quotes and screenshots from Google’s autocomplete algorithms. In doing so, we invite the reader to re-explore Google’s autocomplete algorithms in a creative, playful, and reflexive way, thereby rendering more visible some of the excitement and frivolity that comes from being...
The implementation frameworks of meta-heuristics hybridization with ...
African Journals Online (AJOL)
The hybridization of meta-heuristics algorithms has achieved a remarkable improvement from the adaptation of dynamic parameterization. This paper proposes a variety of implementation frameworks for the hybridization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) and the dynamic parameterization.
Heuristically improved Bayesian segmentation of brain MR images ...
African Journals Online (AJOL)
Hence involving problem specific heuristics and expert knowledge in designing segmentation algorithms seems to be useful. A two-phase segmentation algorithm based on Bayesian method is proposed in this paper. The Bayesian part uses the gray value in segmenting images and the segmented image is used as the
Performance Evaluation of Hyper Threading Technology ...
African Journals Online (AJOL)
PROF. OLIVER OSUAGWA
2015-12-01
Dec 1, 2015 ... This paper describes the Hyper-Threading Technology architecture, and discusses the micro architecture details of Intel's structure. Hyper-Threading Technology is an important addition to. Intel's enterprise product line and has been integrated into a wide variety of products. Intel provides Hyper-Threading ...
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.
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
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
Indian Academy of Sciences (India)
In the description of algorithms and programming languages, what is the role of control abstraction? • What are the inherent limitations of the algorithmic processes? In future articles in this series, we will show that these constructs are powerful and can be used to encode any algorithm. In the next article, we will discuss ...
Multi-threaded Object Streaming
Pfeiffer, Andreas; Govi, Giacomo; Ojeda, Miguel; Sipos, Roland
2015-01-01
The CMS experiment at CERNs Large Hadron Collider in Geneva redesigned the code handling the conditions data during the last years, aiming to increase performance and enhance maintainability. The new design includes a move to serialise all payloads before storing them into the database, allowing the handling of the payloads in external tools independent of a given software release. In this talk we present the results of performance studies done using the serialisation package from the Boost suite as well as serialisation done with the ROOT (v5) tools. Furthermore, as the Boost tools allow parallel (de-)serialisation, we show the performance gains achieved with parallel threads when de-serialising a realistic set of conditions in CMS. Without specific optimisations an overall speed up of a factor of 3-4 was achieved using multi-threaded loading and de-serialisation of our conditions.
Bit Threads and Holographic Entanglement
Freedman, Michael; Headrick, Matthew
2017-05-01
The Ryu-Takayanagi (RT) formula relates the entanglement entropy of a region in a holographic theory to the area of a corresponding bulk minimal surface. Using the max flow-min cut principle, a theorem from network theory, we rewrite the RT formula in a way that does not make reference to the minimal surface. Instead, we invoke the notion of a "flow", defined as a divergenceless norm-bounded vector field, or equivalently a set of Planck-thickness "bit threads". The entanglement entropy of a boundary region is given by the maximum flux out of it of any flow, or equivalently the maximum number of bit threads that can emanate from it. The threads thus represent entanglement between points on the boundary, and naturally implement the holographic principle. As we explain, this new picture clarifies several conceptual puzzles surrounding the RT formula. We give flow-based proofs of strong subadditivity and related properties; unlike the ones based on minimal surfaces, these proofs correspond in a transparent manner to the properties' information-theoretic meanings. We also briefly discuss certain technical advantages that the flows offer over minimal surfaces. In a mathematical appendix, we review the max flow-min cut theorem on networks and on Riemannian manifolds, and prove in the network case that the set of max flows varies Lipshitz continuously in the network parameters.
Heuristic of radiodiagnostic systems
Energy Technology Data Exchange (ETDEWEB)
Wackenheim, A.
1986-12-01
In the practice of creating expert systems, the radiologist and his team are considered as the expert who leads the job of the cognitian or cognitician. Different kinds of expert systems can be imagined. The author describes the main characteristics of heuristics in redefining semiology, semantics and rules of picture reading. Finally it is the experience of the couple expert and cognitician which will in the futur grant for the success of expert systems in radiology.
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.
2015-08-17
Control based on Heuristic Dynamic Programming for Nonlinear Continuous-Time Systems In this paper, a novel predictive event-triggered control...method based on heuristic dynamic programming (HDP) algorithm is developed for nonlinear continuous-time systems. A model network is used to estimate...College Road, Suite II Kingston, RI 02881 -1967 ABSTRACT Predictive Event-Triggered Control based on Heuristic Dynamic Programming for Nonlinear
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.
Bio-Inspired Meta-Heuristics for Emergency Transportation Problems
Directory of Open Access Journals (Sweden)
Min-Xia Zhang
2014-02-01
Full Text Available Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA, particle swarm optimization (PSO, ant colony optimization (ACO, etc., for solving emergency transportation problems. We then propose a new hybrid biogeography-based optimization (BBO algorithm, which outperforms some state-of-the-art heuristics on a typical transportation planning problem.
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)
, i is referred to as the loop-index, 'stat-body' is any sequence of ... while i ~ N do stat-body; i: = i+ 1; endwhile. The algorithm for sorting the numbers is described in Table 1 and the algorithmic steps on a list of 4 numbers shown in. Figure 1.
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.
Threads Pipelining on the CellBE Systems
Directory of Open Access Journals (Sweden)
TANASE, C. A.
2013-08-01
Full Text Available This article aims to describe a model to accelerate the execution of a parallel algorithm implemented on a Cell B.E. processor. The algorithm implements a technique of finding a moving target in a maze with dynamic architecture, using another technique of pipelining the data transfers between the PPU and SPU threads. We have shown that by using the pipelining technique, we can achieve an improvement of the computing time (around 40%. It can be also seen that the pipelining technique with one SPU is about as good as the parallel technique with four SPUs.
The Digital Thread as the Key Enabler
2016-11-01
life cycle by providing the capability to access, integrate and transform disparate data into actionable information. The digital thread is the...17 Defense AT&L: November-December 2016 The Digital Thread as the Key Enabler Col. Keith Bearden, USAF Bearden is the deputy director of...enabling you to do your job better, faster and cheaper. There is one initiative, the key enabler, to accomplish this goal—the digital thread. But let’s
Multi-threaded Object Streaming
Di Guida, Salvatore; Govi, Giacomo; Ojeda, Miguel; Pfeiffer, Andreas; Sipos, Roland
2015-12-01
The CMS experiment at the Large Hadron Collider (LHC) at CERN, Geneva, Switzerland, is made of many detectors which in total sum up to more than 75 million channels. The detector monitoring information of all channels (temperatures, voltages, etc.), detector quality, beam conditions, and other data crucial for the reconstruction and analysis of the experiment's recorded collision events is stored in an online database. A subset of that information, the “conditions data”, is copied out to another database from where it is used in the offline reconstruction and analysis processing, together with alignment data for the various detectors. Conditions data sets are accessed by a tag and an interval of validity through the offline reconstruction program CMSSW, written in C++. About 400 different types of calibration and alignment exist for the various CMS sub-detectors. With the CMS software framework moving to a multi-threaded execution model, and profiting from the experience gained during the data taking in Run-1, a major re-design of the CMS conditions software was done. During this work, a study was done to look into possible gains by using multi-threaded handling of the conditions. In this paper, we present the results of that study.
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…
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.
AthenaMT: upgrading the ATLAS software framework for the many-core world with multi-threading
Leggett, Charles; Baines, John; Bold, Tomasz; Calafiura, Paolo; Farrell, Steven; van Gemmeren, Peter; Malon, David; Ritsch, Elmar; Stewart, Graeme; Snyder, Scott; Tsulaia, Vakhtang; Wynne, Benjamin; ATLAS Collaboration
2017-10-01
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 handling of features such as event and time dependent data, asynchronous callbacks, metadata, integration with the online High Level Trigger for partial processing in certain regions of interest, concurrent I/O, as well as ensuring thread safety of core services. We also report on upgrading the framework to handle Algorithms that are fully re-entrant.
M-machine SDST flow shop scheduling using modified heuristic ...
African Journals Online (AJOL)
A very restricted research has been reported on bi-criteria SDST flow shop scheduling problems dealing with due date related performance measures. In the present work, a modified heuristic based genetic algorithm (MHGA) has been developed for the aforesaid scheduling problem subject to the minimization of weighted ...
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...
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.
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.
Eyebrow threading: A boon or a bane
Directory of Open Access Journals (Sweden)
Sanjeev Gupta
2011-01-01
Full Text Available Eyebrow threading is a practice of shaping the eyebrows. Many dermatological complications have been briefly mentioned in various publications. There are scant data regarding the appearance of molluscum in the line of eyebrows after a session of threading. We report a series of eight patients both males (3 and females (5 who had lesions of molluscum in the eyebrow region after threading. The earlier reported cases are only among the females. The present study is highlighting the appearance of molluscum in the region of eyebrow after a session of threading from beauty salon. So, to the best of our knowledge, this is the first report of its kind describing same pathology in males. The rational of reporting this case series is to create awareness among the dermatologists as well as in general population about potential hazards of threading.
Indian Academy of Sciences (India)
Algorithms. 3. Procedures and Recursion. R K Shyamasundar. In this article we introduce procedural abstraction and illustrate its uses. Further, we illustrate the notion of recursion which is one of the most useful features of procedural abstraction. Procedures. Let us consider a variation of the pro blem of summing the first M.
Indian Academy of Sciences (India)
number of elements. We shall illustrate the widely used matrix multiplication algorithm using the two dimensional arrays in the following. Consider two matrices A and B of integer type with di- mensions m x nand n x p respectively. Then, multiplication of. A by B denoted, A x B , is defined by matrix C of dimension m xp where.
Triplet supertree heuristics for the tree of life.
Lin, Harris T; Burleigh, J Gordon; Eulenstein, Oliver
2009-01-30
There is much interest in developing fast and accurate supertree methods to infer the tree of life. Supertree methods combine smaller input trees with overlapping sets of taxa to make a comprehensive phylogenetic tree that contains all of the taxa in the input trees. The intrinsically hard triplet supertree problem takes a collection of input species trees and seeks a species tree (supertree) that maximizes the number of triplet subtrees that it shares with the input trees. However, the utility of this supertree problem has been limited by a lack of efficient and effective heuristics. We introduce fast hill-climbing heuristics for the triplet supertree problem that perform a step-wise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. To realize time efficient heuristics we designed the first nontrivial algorithms for two standard search problems, which greatly improve on the time complexity to the best known (naïve) solutions by a factor of n and n2 (the number of taxa in the supertree). These algorithms enable large-scale supertree analyses based on the triplet supertree problem that were previously not possible. We implemented hill-climbing heuristics that are based on our new algorithms, and in analyses of two published supertree data sets, we demonstrate that our new heuristics outperform other standard supertree methods in maximizing the number of triplets shared with the input trees. With our new heuristics, the triplet supertree problem is now computationally more tractable for large-scale supertree analyses, and it provides a potentially more accurate alternative to existing supertree methods.
Superiorization: an optimization heuristic for medical physics.
Herman, Gabor T; Garduno, Edgar; Davidi, Ran; Censor, Yair
2012-09-01
To describe and mathematically validate the superiorization methodology, which is a recently developed heuristic approach to optimization, and to discuss its applicability to medical physics problem formulations that specify the desired solution (of physically given or otherwise obtained constraints) by an optimization criterion. The superiorization methodology is presented as a heuristic solver for a large class of constrained optimization problems. The constraints come from the desire to produce a solution that is constraints-compatible, in the sense of meeting requirements provided by physically or otherwise obtained constraints. The underlying idea is that many iterative algorithms for finding such a solution are perturbation resilient in the sense that, even if certain kinds of changes are made at the end of each iterative step, the algorithm still produces a constraints-compatible solution. This property is exploited by using permitted changes to steer the algorithm to a solution that is not only constraints-compatible, but is also desirable according to a specified optimization criterion. The approach is very general, it is applicable to many iterative procedures and optimization criteria used in medical physics. The main practical contribution is a procedure for automatically producing from any given iterative algorithm its superiorized version, which will supply solutions that are superior according to a given optimization criterion. It is shown that if the original iterative algorithm satisfies certain mathematical conditions, then the output of its superiorized version is guaranteed to be as constraints-compatible as the output of the original algorithm, but it is superior to the latter according to the optimization criterion. This intuitive description is made precise in the paper and the stated claims are rigorously proved. Superiorization is illustrated on simulated computerized tomography data of a head cross section and, in spite of its generality
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...
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
Improper assignment of gates may result in flight delays, inefficient use of the resource, customer’s dissatisfaction. A typical metropolitan airport handles hundreds of flights a day. Solving the gate assignment problem (GAP) to optimality is often impractical. Meta-heuristics have recently been...... 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...
Formative Research on the Heuristic Task Analysis.
Reigeluth, Charles M.; Lee, Ji-Yeon; Peterson, Bruce; Chavez, Michael
Corporate and educational settings increasingly require decision-making, problem-solving and other complex cognitive skills to handle ill-structured, or heuristic, tasks, but the growing need for heuristic task expertise has outpaced the refinement of task analysis methods for heuristic expertise. The Heuristic Task Analysis (HTA) Method was…
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
A novel hybrid meta-heuristic technique applied to the well-known benchmark optimization problems
Abtahi, Amir-Reza; Bijari, Afsane
2017-09-01
In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition, the proposed hybrid algorithm uses SA to make a balance between exploration and exploitation phases. The proposed hybrid algorithm is compared with several meta-heuristic methods, including genetic algorithm (GA), HS, and ICA on several well-known benchmark instances. The comprehensive experiments and statistical analysis on standard benchmark functions certify the superiority of the proposed method over the other algorithms. The efficacy of the proposed hybrid algorithm is promising and can be used in several real-life engineering and management problems.
Thread as a matrix for biomedical assays.
Reches, Meital; Mirica, Katherine A; Dasgupta, Rohit; Dickey, Michael D; Butte, Manish J; Whitesides, George M
2010-06-01
This paper describes the use of thread as a matrix for the fabrication of diagnostic assay systems. The kinds of thread used for this study are inexpensive, broadly available, and lightweight; some of them are already familiar materials in healthcare. Fluids wick along these threads by capillary action; no external power source is necessary for pumping. This paper demonstrates three designs for diagnostic assays that use different characteristics of the thread. The first two designs-the "woven array" and the "branching design"-take advantage of the ease with which thread can be woven on a loom to generate fluidic pathways that enable multiple assays to be performed in parallel. The third design-the "sewn array"-takes advantage of the ease with which thread can be sewn through a hydrophobic polymer sheet to incorporate assays into bandages, diapers and similar systems. These designs lead to microfluidic devices that may be useful in performing simple colorimetric assays that require qualitative results. We demonstrate the function of thread-based microfluidic devices in the context of five different colorimetric assays: detection of ketones, nitrite, protein, and glucose in artificial urine, and detection of alkaline phosphatase in artificial plasma.
Heuristic Methods for Security Protocols
Directory of Open Access Journals (Sweden)
Qurat ul Ain Nizamani
2009-10-01
Full Text Available Model checking is an automatic verification technique to verify hardware and software systems. However it suffers from state-space explosion problem. In this paper we address this problem in the context of cryptographic protocols by proposing a security property-dependent heuristic. The heuristic weights the state space by exploiting the security formulae; the weights may then be used to explore the state space when searching for attacks.
Electroanalytical devices with pins and thread.
Glavan, Ana C; Ainla, Alar; Hamedi, Mahiar M; Fernández-Abedul, M Teresa; Whitesides, George M
2016-01-07
This work describes the adaptive use of conventional stainless steel pins-used in unmodified form or coated with carbon paste-as working, counter, and quasi-reference electrodes in electrochemical devices fabricated using cotton thread or embossed omniphobic R(F) paper to contain the electrolyte and sample. For some applications, these pin electrodes may be easier to modify and use than printed electrodes, and their position and orientation can be changed as needed. Electroanalytical devices capable of multiplex analysis (thread-based arrays or 96-well plates) were easily fabricated using pins as electrodes in either thread or omniphobic R(F) paper.
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.
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
Facial thread lifting with suture suspension
National Research Council Canada - National Science Library
Joana de Pinho Tavares; Carlos Augusto Costa Pires Oliveira; Rodolfo Prado Torres; Fayez Bahmad Jr
...: To analyze data published in the literature on the durability of results, their effectiveness, safety, and risk of serious adverse events associated with procedures using several types of threading sutures. Methods...
Drill pipe threaded nipple connection design development
Saruev, Aleksey Lvovich; Saruev, Lev Alekseevich; Vasenin, S. S.
2015-01-01
The paper presents the analysis of the behavior of the drill pipe nipple connection under the additional load generated by power pulses. The strain wave propagation through the nipple thread connection of drill pipes to the bottomhole is studied in this paper. The improved design of the nipple thread connection is suggested using the obtained experimental and theoretical data. The suggested connection design allows not only the efficient transmission of strain wave energy to a drill bit but a...
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.
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.
46 CFR 56.30-20 - Threaded joints.
2010-10-01
... 46 Shipping 2 2010-10-01 2010-10-01 false Threaded joints. 56.30-20 Section 56.30-20 Shipping... APPURTENANCES Selection and Limitations of Piping Joints § 56.30-20 Threaded joints. (a) Threaded joints may be... other than taper pipe threads may be used for piping components where tightness of the joint depends on...
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.
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.
A Heuristic for Disassembly Planning in Remanufacturing System
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Jinmo Sung
2014-01-01
Full Text Available This study aims to improve the efficiency of disassembly planning in remanufacturing environment. Even though disassembly processes are considered as the reverse of the corresponding assembly processes, under some technological and management constraints the feasible and efficient disassembly planning can be achieved by only well-designed algorithms. In this paper, we propose a heuristic for disassembly planning with the existence of disassembled part/subassembly demands. A mathematical model is formulated for solving this problem to determine the sequence and quantity of disassembly operations to minimize the disassembly costs under sequence-dependent setup and capacity constraints. The disassembly costs consist of the setup cost, part inventory holding cost, disassembly processing cost, and purchasing cost that resulted from unsatisfied demand. A simple but efficient heuristic algorithm is proposed to improve the quality of solution and computational efficiency. The main idea of heuristic is to divide the planning horizon into the smaller planning windows and improve the computational efficiency without much loss of solution quality. Performances of the heuristic are investigated through the computational experiments.
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.
Recent Advances in Solving the Protein Threading Problem
Andonov, Rumen; Gibrat, Jean-François; Marin, Antoine; Poirriez, Vincent; Yanev, Nikola
2007-01-01
The fold recognition methods are promissing tools for capturing the structure of a protein by its amino acid residues sequence but their use is still restricted by the needs of huge computational resources and suitable efficient algorithms as well. In the recent version of FROST (Fold Recognition Oriented Search Tool) package the most efficient algorithm for solving the Protein Threading Problem (PTP) is implemented due to the strong collaboration between the SYMBIOSE group in IRISA and MIG in Jouy-en-Josas. In this paper, we present the diverse components of FROST, emphasizing on the recent advances in formulating and solving new versions of the PTP and on the way of solving on a computer cluster a million of instances in a easonable time.
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...
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
An Ant Colony based Hyper-Heuristic Approach for the Set Covering Problem
Directory of Open Access Journals (Sweden)
Alexandre Silvestre FERREIRA
2015-12-01
Full Text Available The Set Covering Problem (SCP is a NP-hard combinatorial optimization problem that is challenging for meta-heuristic algorithms. In the optimization literature, several approaches using meta-heuristics have been developed to tackle the SCP and the quality of the results provided by these approaches highly depends on customized operators that demands high effort from researchers and practitioners. In order to alleviate the complexity of designing metaheuristics, a methodology called hyper-heuristic has emerged as a possible solution. A hyper-heuristic is capable of dynamically selecting simple low-level heuristics accordingly to their performance, alleviating the design complexity of the problem solver and obtaining satisfactory results at the same time. In a previous study, we proposed a hyper-heuristic approach based on Ant Colony Optimization (ACO-HH for solving the SCP. This paper extends our previous efforts, presenting better results and a deeper analysis of ACO-HH parameters and behavior, specially about the selection of low-level heuristics. The paper also presents a comparison with an ACO meta-heuristic customized for the SCP.
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.
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
Facial thread lifting with suture suspension
Directory of Open Access Journals (Sweden)
Joana de Pinho Tavares
Full Text Available Abstract Introduction: The increased interest in minimally-invasive treatments, such as the thread lifting, with lower risk of complications, minimum length of time away from work and effectiveness in correcting ptosis and aging characteristics has led many specialists to adopt this technique, but many doubts about its safety and effectiveness still limit its overall use. Objective: To analyze data published in the literature on the durability of results, their effectiveness, safety, and risk of serious adverse events associated with procedures using several types of threading sutures. Methods: Literature review using the key words "thread lift", "barbed suture", "suture suspension" and "APTOS". Due to the scarcity of literature, recent reports of facial lifting using threads were also selected, complemented with bibliographical references. Result: The first outcomes of facial lifting with barbed sutures remain inconclusive. Adverse events may occur, although they are mostly minor, self-limiting, and short-lived. The data on the maximum effect of the correction, the durability of results, and the consequences of the long-term suture stay are yet to be clarified. Conclusion: Interest in thread lifting is currently high, but this review suggests that it should not yet be adopted as an alternative to rhytidectomy.
Facial thread lifting with suture suspension.
Tavares, Joana de Pinho; Oliveira, Carlos Augusto Costa Pires; Torres, Rodolfo Prado; Bahmad, Fayez
2017-05-09
The increased interest in minimally-invasive treatments, such as the thread lifting, with lower risk of complications, minimum length of time away from work and effectiveness in correcting ptosis and aging characteristics has led many specialists to adopt this technique, but many doubts about its safety and effectiveness still limit its overall use. To analyze data published in the literature on the durability of results, their effectiveness, safety, and risk of serious adverse events associated with procedures using several types of threading sutures. Literature review using the key words "thread lift", "barbed suture", "suture suspension" and "APTOS". Due to the scarcity of literature, recent reports of facial lifting using threads were also selected, complemented with bibliographical references. The first outcomes of facial lifting with barbed sutures remain inconclusive. Adverse events may occur, although they are mostly minor, self-limiting, and short-lived. The data on the maximum effect of the correction, the durability of results, and the consequences of the long-term suture stay are yet to be clarified. Interest in thread lifting is currently high, but this review suggests that it should not yet be adopted as an alternative to rhytidectomy. Copyright © 2017 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.
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.
Conflict and Bias in Heuristic Judgment
Bhatia, Sudeep
2017-01-01
Conflict has been hypothesized to play a key role in recruiting deliberative processing in reasoning and judgment tasks. This claim suggests that changing the task so as to add incorrect heuristic responses that conflict with existing heuristic responses can make individuals less likely to respond heuristically and can increase response accuracy.…
An Effective Exercise for Teaching Cognitive Heuristics
Swinkels, Alan
2003-01-01
This article describes a brief heuristics demonstration and offers suggestions for personalizing examples of heuristics by making them relevant to students. Students complete a handout asking for 4 judgments illustrative of such heuristics. The decisions are cast in the context of students' daily lives at their particular university. After the…
Automatic Choice of Scheduling Heuristics for Parallel/Distributed Computing
Directory of Open Access Journals (Sweden)
Clayton S. Ferner
1999-01-01
Full Text Available Task mapping and scheduling are two very difficult problems that must be addressed when a sequential program is transformed into a parallel program. Since these problems are NP‐hard, compiler writers have opted to concentrate their efforts on optimizations that produce immediate gains in performance. As a result, current parallelizing compilers either use very simple methods to deal with task scheduling or they simply ignore it altogether. Unfortunately, the programmer does not have this luxury. The burden of repartitioning or rescheduling, should the compiler produce inefficient parallel code, lies entirely with the programmer. We were able to create an algorithm (called a metaheuristic, which automatically chooses a scheduling heuristic for each input program. The metaheuristic produces better schedules in general than the heuristics upon which it is based. This technique was tested on a suite of real scientific programs written in SISAL and simulated on four different network configurations. Averaged over all of the test cases, the metaheuristic out‐performed all eight underlying scheduling algorithms; beating the best one by 2%, 12%, 13%, and 3% on the four separate network configurations. It is able to do this, not always by picking the best heuristic, but rather by avoiding the heuristics when they would produce very poor schedules. For example, while the metaheuristic only picked the best algorithm about 50% of the time for the 100 Gbps Ethernet, its worst decision was only 49% away from optimal. In contrast, the best of the eight scheduling algorithms was optimal 30% of the time, but its worst decision was 844% away from optimal.
Viscous thread behavior in branching microchannels
Cubaud, Thomas; Hu, Xiaoyi; Sauzade, Martin
2014-11-01
We experimentally study the properties of viscous core-annular flows using miscible fluids in bifurcating microchannels. A viscous filament is first generated using a square hydrodynamic focusing junction by injecting a thick fluid into the central channel and a thin fluid from the side-channels. This method allows us to produce miscible fluid threads of various sizes and lateral positions in the channel, and enables the systematic study of thread transport and stability from low to moderate Reynolds numbers in branching microfluidic networks. We examine, in particular, the role of viscous buckling instabilities on thread behavior and the formation of complex viscous mixtures and stratifications at the small-scale. This work is supported by NSF (CBET-1150389).
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.
Heuristics for Multidimensional Packing Problems
DEFF Research Database (Denmark)
Egeblad, Jens
for a three-dimensional knapsack packing problem involving furniture is presented in the fourth paper. The heuristic is based on a variety of techniques including tree-search, wall-building, and sequential placement. The solution process includes considerations regarding stability and load bearing strength...
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…
A multi-thread scheduling method for 3D CT image reconstruction using multi-GPU.
Zhu, Yining; Zhao, Yunsong; Zhao, Xing
2012-01-01
As a whole process, we present a concept that the complete reconstruction of CT image should include the computation part on GPUs and the data storage part on hard disks. From this point of view, we propose a Multi-Thread Scheduling (MTS) method to implement the 3D CT image reconstruction such as using FDK algorithm, to trade off the computing and storage time. In this method we use Multi-Threads to control GPUs and a separate thread to accomplish data storage, so that we make the calculation and data storage simultaneously. In addition, we use the 4-channel texture to maintain symmetrical projection data in CUDA framework, which can reduce the calculation time significantly. Numerical experiment shows that the time for the whole process with our method is almost the same as the data storage time.
The 3D CT image reconstruction based on multi-thread scheduling using multi-GPU
Zhu, Yining; Zhao, Yunsong; Zhao, Xing
2012-03-01
In this paper, we express a concept that the complete reconstruction process should include the computation part on GPUs and the data storage part. We propose a multi-thread scheduling (MTS) method to implement the FDK algorithm, to coordinate?? the computing and storage time. In this method we use multi0-threads to control the GPUs and a separate thread to accomplish data storage, so as to cover the calculation and data storage in time process. In addition, we use the four-channel texture to maintain symmetrical projection data in CUDA framework, which can reduce the calculation time significantly.. Numerical experiment shows that the time cost of the whole process with our method is almost the same as the data storage time cost.
Drill pipe threaded nipple connection design development
Saruev, A. L.; Saruev, L. A.; Vasenin, S. S.
2015-11-01
The paper presents the analysis of the behavior of the drill pipe nipple connection under the additional load generated by power pulses. The strain wave propagation through the nipple thread connection of drill pipes to the bottomhole is studied in this paper. The improved design of the nipple thread connection is suggested using the obtained experimental and theoretical data. The suggested connection design allows not only the efficient transmission of strain wave energy to a drill bit but also the automation of making-up and breaking-out drill pipes.
Hermawati, Setia; Lawson, Glyn
2016-01-01
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 i...
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.
Heuristics for Relevancy Ranking of Earth Dataset Search Results
Lynnes, C.; Quinn, P.; Norton, J.
2016-12-01
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.
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.
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).
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
of the optimal algorithms we have tested. In particular, GRASP Sorted shows the most promising performance, as it is able to find solutions that are both agile (sorted) and well balanced, and consistently yields the best numerical performance among the developed algorithms....... 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...
Threading plasmonic nanoparticle strings with light.
Herrmann, Lars O; Valev, Ventsislav K; Tserkezis, Christos; Barnard, Jonathan S; Kasera, Setu; Scherman, Oren A; Aizpurua, Javier; Baumberg, Jeremy J
2014-07-28
Nanomaterials find increasing application in communications, renewable energies, electronics and sensing. Because of its unsurpassed speed and highly tuneable interaction with matter, using light to guide the self-assembly of nanomaterials can open up novel technological frontiers. However, large-scale light-induced assembly remains challenging. Here we demonstrate an efficient route to nano-assembly through plasmon-induced laser threading of gold nanoparticle strings, producing conducting threads 12±2 nm wide. This precision is achieved because the nanoparticles are first chemically assembled into chains with rigidly controlled separations of 0.9 nm primed for re-sculpting. Laser-induced threading occurs on a large scale in water, tracked via a new optical resonance in the near-infrared corresponding to a hybrid chain/rod-like charge transfer plasmon. The nano-thread width depends on the chain mode resonances, the nanoparticle size, the chain length and the peak laser power, enabling nanometre-scale tuning of the optical and conducting properties of such nanomaterials.
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
Performance Evaluation of Hyper Threading Technology ...
African Journals Online (AJOL)
We then use the PM data to make deduction on a new metric of efficiency in order to quantify processor resource utilization and make comparisons of that utilization between single-threading (ST) and HT modes. We also study performance gain using unhalted core cycles, code efficiency of using vector units of the ...
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.
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 Moiré Pattern-Based Thread Counter
Reich, Gary
2017-01-01
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…
Précis of Simple heuristics that make us smart.
Todd, P M; Gigerenzer, G
2000-10-01
How can anyone be rational in a world where knowledge is limited, time is pressing, and deep thought is often an unattainable luxury? Traditional models of unbounded rationality and optimization in cognitive science, economics, and animal behavior have tended to view decision-makers as possessing supernatural powers of reason, limitless knowledge, and endless time. But understanding decisions in the real world requires a more psychologically plausible notion of bounded rationality. In Simple heuristics that make us smart (Gigerenzer et al. 1999), we explore fast and frugal heuristics--simple rules in the mind's adaptive toolbox for making decisions with realistic mental resources. These heuristics can enable both living organisms and artificial systems to make smart choices quickly and with a minimum of information by exploiting the way that information is structured in particular environments. In this précis, we show how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristics for sequential search. These simple heuristics perform comparably to more complex algorithms, particularly when generalizing to new data--that is, simplicity leads to robustness. We present evidence regarding when people use simple heuristics and describe the challenges to be addressed by this research program.
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.
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…
Automatic design of decision-tree algorithms with evolutionary algorithms.
Barros, Rodrigo C; Basgalupp, Márcio P; de Carvalho, André C P L F; Freitas, Alex A
2013-01-01
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. The algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.
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.
Solving the Tractor and Semi-Trailer Routing Problem Based on a Heuristic Approach
Directory of Open Access Journals (Sweden)
Hongqi Li
2012-01-01
Full Text Available We study the tractor and semi-trailer routing problem (TSRP, a variant of the vehicle routing problem (VRP. In the TSRP model for this paper, vehicles are dispatched on a trailer-flow network where there is only one main depot, and all tractors originate and terminate in the main depot. Two types of decisions are involved: the number of tractors and the route of each tractor. Heuristic algorithms have seen widespread application to various extensions of the VRP. However, this approach has not been applied to the TSRP. We propose a heuristic algorithm to solve the TSRP. The proposed heuristic algorithm first constructs the initial route set by the limitation of a driver’s on-duty time. The candidate routes in the initial set are then filtered by a two-phase approach. The computational study shows that our algorithm is feasible for the TSRP. Moreover, the algorithm takes relatively little time to obtain satisfactory solutions. The results suggest that our heuristic algorithm is competitive in solving the TSRP.
Directory of Open Access Journals (Sweden)
Lopez-Loces Mario C.
2016-06-01
Full Text Available Internet shopping has been one of the most common online activities, carried out by millions of users every day. As the number of available offers grows, the difficulty in getting the best one among all the shops increases as well. In this paper we propose an integer linear programming (ILP model and two heuristic solutions, the MinMin algorithm and the cellular processing algorithm, to tackle the Internet shopping optimization problem with delivery costs. The obtained results improve those achieved by the state-of-the-art heuristics, and for small real case scenarios ILP delivers exact solutions in a reasonable amount of time.
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.
Bellala, Djamel; Smadi, Hacene; Medjghou, Aicha
Exact solutions for the TSP problem are typically difficult from computational point of view, because of their size and time complexities. That is why, heuristics are substituted to exact algorithms in order to provide a good solution to the problem. In this paper two heuristics, the nearest-neighbor and the subtour-reversal algorithms, are used to solve an industrial problem. The first algorithm gives birth to an optimal tour by which the industrial process can be carried out while the second algorithm generally provides an improvement to the previous optimal tour.
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).
Ali, Yasser Helmy
2017-09-01
Thread lifting rejuvenation procedures are re-evolved again, after developing of absorbable threads, with very popular spread among plastic surgeons and dermatologists but with little articles have been written in literature about absorbable threads. Objective to evaluate two years' outcome of absorbable barbed thread lifting used for facial rejuvenation. Prospective comparative study both objectively and subjectively and follow up assessment for 24 months. Thread lifting for face rejuvenation has significant long-lasting considerable 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 rejuvenations are got by thread lifting and highly augmented results are observed when they are combined with Botox, fillers and/or platelet rich plasma (PRP) rejuvenations.
The entity-to-algorithm allocation problem: Extending the analysis
CSIR Research Space (South Africa)
Grobler, J
2014-12-01
Full Text Available This paper extends the investigation into the algorithm selection problem in hyper-heuristics, otherwise referred to as the entity-to-algorithm allocation problem, introduced by Grobler et al.. Two newly developed population-based portfolio...
Directory of Open Access Journals (Sweden)
Mehmet Fatih Tasgetiren
2016-10-01
Full Text Available In this paper, we present a variable block insertion heuristic (VBIH algorithm to solve the blocking flowshop scheduling problem with the total flowtime criterion. In the VBIH algorithm, we define a minimum and a maximum block size. After constructing the initial sequence, the VBIH algorithm starts with a minimum block size being equal to one. It removes the block from the current sequence and inserts it into the partial sequence sequentially with a predetermined move size. The sequence, which is obtained after several block moves, goes under a variable local search (VLS, which is based on traditional insertion and swap neighborhood structures. If the new sequence obtained after the VLS local search is better than the current sequence, it replaces the current sequence. As long as it improves, it keeps the same block size. However, if it does not improve, the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the current sequence. This process is repeated until the block size reaches at the maximum block size. Furthermore, we present a novel constructive heuristic, which is based on the profile fitting heuristic from the literature. The proposed constructive heuristic is able to further improve the best known solutions for some larger instances in a few seconds. Parameters of the constructive heuristic and the VBIH algorithm are determined through a design of experiment approach. Extensive computational results on the Taillard’s well-known benchmark suite show that the proposed VBIH algorithm outperforms the discrete artificial bee colony algorithm, which is one of the most efficient algorithms recently in the literature. Ultimately, 52 out of the 150 best known solutions are further improved with substantial margins.
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.
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
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
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.
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.
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.
Directory of Open Access Journals (Sweden)
Vinícius Vilar Jacob
2016-01-01
Full Text Available This paper addresses a single-machine scheduling problem with sequence-dependent family setup times. In this problem the jobs are classified into families according to their similarity characteristics. Setup times are required on each occasion when the machine switches from processing jobs in one family to jobs in another family. The performance measure to be minimized is the total tardiness with respect to the given due dates of the jobs. The problem is classified as NP-hard in the ordinary sense. Since the computational complexity associated with the mathematical formulation of the problem makes it difficult for optimization solvers to deal with large-sized instances in reasonable solution time, efficient heuristic algorithms are needed to obtain near-optimal solutions. In this work we propose three heuristics based on the Iterated Local Search (ILS metaheuristic. The first heuristic is a basic ILS, the second uses a dynamic perturbation size, and the third uses a Path Relinking (PR technique as an intensification strategy. We carry out comprehensive computational and statistical experiments in order to analyze the performance of the proposed heuristics. The computational experiments show that the ILS heuristics outperform a genetic algorithm proposed in the literature. The ILS heuristic with dynamic perturbation size and PR intensification has a superior performance compared to other heuristics.
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.
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.
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
DEFF Research Database (Denmark)
Ding, Yi; Goel, Lalit; Wang, Peng
2012-01-01
the required level of supply reliability to its customers. In previous research, Genetic Algorithm (GA) has been used to solve most reliability optimization problems. However, the GA is not very computationally efficient in some cases. In this chapter a new heuristic optimization technique—the particle swarm...
A NONLINEAR FEASIBILITY PROBLEM HEURISTIC
Directory of Open Access Journals (Sweden)
Sergio Drumond Ventura
2015-04-01
Full Text Available In this work we consider a region S ⊂ given by a finite number of nonlinear smooth convex inequalities and having nonempty interior. We assume a point x 0 is given, which is close in certain norm to the analytic center of S, and that a new nonlinear smooth convex inequality is added to those defining S (perturbed region. It is constructively shown how to obtain a shift of the right-hand side of this inequality such that the point x 0 is still close (in the same norm to the analytic center of this shifted region. Starting from this point and using the theoretical results shown, we develop a heuristic that allows us to obtain the approximate analytic center of the perturbed region. Then, we present a procedure to solve the problem of nonlinear feasibility. The procedure was implemented and we performed some numerical tests for the quadratic (random case.
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.
Operational Thread Development: A Structured Approach to Capability Analysis
National Research Council Canada - National Science Library
Hamilton, Scott; Solterbeck, William; Wright, Jean
2006-01-01
This paper will introduce the Operational Thread Development (OTD) methodology for analyzing warfighting capability and assessing the contribution of potential solutions to filling identified capability deficiencies...
The Analysis of Design Parameters of Thread Milling Cutters
Directory of Open Access Journals (Sweden)
O. V. Malkov
2015-01-01
Full Text Available Now the mechanical engineering industry produces a great variety of part mix having a male and female thread. In this regard a relevant task is to choose the most effective way of threading. Introduction of multi-coordinate CNC machines considerably extended the use of thread mills, instead of taps, roll burnishers, dies and thread turning tools.The article reviews manufacturer’s production programs of thread mills (Carmex, Emuge, Jel, Sandvik, Vargus to show that, presently, there is a significant diversity of thread mill designs for processing. The analysis allowed to reveal the main nomenclature and standard sizes of thread mills, including combined tools on their base, as well as to reveal classification signs and to develop classification of thread mills. Classification comprises also combined tools based on design of thread mill, which allow us to reduce the nomenclature of the tools used in threading.The paper considers working schemes of the main types of thread mills and areas of their rational application.To analyse design data of thread mills two types of tools have been selected, namely the integral trailer edge thread mills with the spiral chip flutes and drill thread mills made from hard alloy. The analysis of design data was made in the closed "system of the tool", i.e. in advance assuming that there is a connection between diameter of the tapping part of the tool and diameter of the cut thread. The parameter analysis of the chosen designs allowed us to develop the sketches of tools with the specified parameters to be calculated.The paper presents graphic dependences of the total length, length of a working part, diameter of a tail part and number of tool teeth on the diameter of the working part of the tool. Approximation of the specified parameters is carried out and mathematical dependences, which can be further used to calculate and choose the starting values of design data in designing the abovementioned constructions of
Shape and stability of a viscous thread
DEFF Research Database (Denmark)
Bohr, Tomas; Senchenko, Sergey
2005-01-01
When a viscous fluid, like oil or syrup, streams from a small orifice and falls freely under gravity, it forms a long slender thread, which can be maintained in a stable, stationary state with lengths up to several meters. We discuss the shape of such liquid threads and their surprising stability....... The stationary shapes are discussed within the long-wavelength approximation and compared to experiments. It turns out that the strong advection of the falling fluid can almost outrun the Rayleigh-Plateau instability. The asymptotic shape and stability are independent of viscosity and small perturbations grow...... with time as exp(Ct(1/4)), where the constant is independent of viscosity. The corresponding spatial growth has the form exp[(z/L)(1/8)], where z is the down stream distance and L similar to Q(2)sigma(-2)g and where sigma is the surface tension divided by density, g is the gravity, and Q is the flux. We...
Capillary breakup of fluid threads within confinement
Hu, Guoqing; Xue, Chundong; Chen, Xiaodong
2016-11-01
Fluid thread breakup is a widespread phenomenon in nature, industry, and daily life. Driven by surface tension (or capillarity) at low flow-rate condition, the breakup scenario is usually called capillary instability or Plateau-Rayleigh instability. Fluid thread deforms under confinement of ambient fluid to form a fluid neck. Thinning of the neck at low flow-rate condition is quasistatic until the interface becomes unstable and collapses to breakup. Underlying mechanisms and universalities of both the stable and unstable thinning remain, however, unclear and even contradictory. Here we conduct new numerical and experimental studies to show that confined interfaces are not only stabilized but also destabilized by capillarity at low flow-rate condition. Capillary stabilization is attributed to confinement-determined internal pressure that is higher than capillary pressure along the neck. Two origins of capillary destabilization are identified: one is confinement-induced gradient of capillary pressure along the interface; the other is the competition between local capillary pressure and internal pressure. This work was supported by National Natural Science Foundation of China (Grant No. 11402274, 11272321, and 11572334).
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.
A hybrid shifting bottleneck-tabu search heuristic for the job shop total weighted tardiness problem
Bülbül, Kerem; Bulbul, Kerem
2010-01-01
In this paper, we study the job shop scheduling problem with the objective of minimizing the total weighted tardiness. We propose a hybrid shifting bottleneck - tabu search (SB-TS) algorithm by replacing the reoptimization step in the shifting bottleneck (SB) algorithm by a tabu search (TS). In terms of the shifting bottleneck heuristic, the proposed tabu search optimizes the total weighted tardiness for partial schedules in which some machines are currently assumed to have infinite capacity...
A heuristic for the minimization of open stacks problem
Directory of Open Access Journals (Sweden)
Fernando Masanori Ashikaga
2009-08-01
Full Text Available It is suggested here a fast and easy to implement heuristic for the minimization of open stacks problem (MOSP. The problem is modeled as a traversing problem in a graph (Gmosp with a special structure (Yanasse, 1997b. It was observed in Ashikaga (2001 that, in the mean experimental case, Gmosp has large cliques and high edge density. This information was used to implement a heuristic based on the extension-rotation algorithm of Pósa (1976 for approximation of Hamiltonian Circuits. Additionally, an initial path for Pósa's algorithm is derived from the vertices of an ideally maximum clique in order to accelerate the process. Extensive computational tests show that the resulting simple approach dominates in time and mean error the fast actually know Yuen (1991 and 1995 heuristic to the problem.Sugerimos uma heurística rápida e de implementação simples para o problema de minimização de pilhas abertas (MOSP. O problema é modelado como um problema de percorrimento de arcos no grafo (Gmosp associado (Yanasse, 1997b. Foi observado em Ashikaga (2001 que o grafo Gmosp possui grandes cliques e uma alta densidade de arestas. Esta informação foi utilizada para implementar uma heurística baseada no algoritmo Extensão-Rotação de Pósa (1976 para aproximação de Circuitos Hamiltonianos. O caminho inicial para o algoritmo de Pósa é obtido a partir dos vértices de uma aproximação do maior clique do grafo para acelerar o processo. Testes computacionais extensivos mostram que a abordagem domina tanto em tempo quanto em erro médio a mais rápida heurística conhecida de Yuen (1991 e 1995.
Formative Research on the Heuristic Task Analysis Process.
Reigeluth, Charles M.; Lee, Ji-Yeon; Peterson, Bruce; Chavez, Michael
Corporate and educational settings increasingly require decision making, problem solving and other complex cognitive skills to handle ill-structured, or heuristic, tasks, but the growing need for heuristic task expertise has outpaced the refinement of task analysis methods for heuristic expertise. The Heuristic Task Analysis (HTA) Method was…
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.
Solving Inventory Routing Problems Using Location Based Heuristics
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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
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.
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.
Judgements with errors lead to behavioral heuristics
Ungureanu, S.
2016-01-01
A decision process robust to errors in the estimation of values, probabilities and times will employ heuristics that generate consistent apparent biases like loss aversion, nonlinear probability weighting with discontinuities and present bias.
Confidentiality for Probabilistic Multi-Threaded Programs and Its Verification
Ngo, Minh Tri; Stoelinga, Mariëlle Ida Antoinette; Huisman, Marieke
2012-01-01
Confidentiality is an important concern in today's information society: electronic payment and personal data should be protected appropriately. This holds in particular for multi-threaded applications, which are generally seen the future of high-performance computing. Multi-threading poses new
Measurement of Threads by Scanning on Coordinate Measuring Machines
DEFF Research Database (Denmark)
Carmignato, Simone; Savio, Enrico; De Chiffre, Leonardo
2003-01-01
This paper presents the latest developments on a new method for the calibration of thread gauges by scanning of thread profiles on coordinate measuring machines. The method is compared with other traditional techniques for discussion of advantages and harmonisation of measuring results...
Confidentiality for Probabilistic Multi-Threaded Programs and Its Verification
Ngo, Minh Tri; Stoelinga, Mariëlle Ida Antoinette; Huisman, Marieke
Confidentiality is an important concern in today’s informa- tion society: electronic payment and personal data should be protected appropriately. This holds in particular for multi-threaded applications, which are generally seen the future of high-performance computing. Multi- threading poses new
A Heuristic Framework to Solve a General Delivery Problem
Lian, Lian; Castelain, Emmanuel
2010-06-01
This paper presents a new distribution and route planning problem, General Delivery Problem (GDP) which is more general than the well-known Vehicle Routing Problem. To solve a GDP, a three-phase framework heuristic approach based on decomposition techniques is introduced. The decomposition techniques are employed to divide an original problem into a set of sub-problems, which can reduce the problem size. A kind of decomposition technique, Capacity Clustering Algorithm (CCA), is embedded into the framework with Simulated Annealing (SA) to solve a special GDP. The proposed three-phase framework with the above two algorithms is compared with five other decomposition methods in a distribution instance of the Regional Fire and Emergency Center in the north of France.
Heuristics and Biases in Retirement Savings Behavior
Shlomo Benartzi; Richard Thaler
2007-01-01
Standard economic theories of saving implicitly assume that households have the cognitive ability to solve the relevant optimization problem and the willpower to execute the optimal plan. Both of the implicit assumptions are suspect. Even among economists, few spend much time calculating a personal optimal savings rate. Instead, most people cope by adopting simple heuristics, or rules of thumb. In this paper, we investigate both the heuristics and the biases that emerge in the area of retirem...
Case Based Heuristic Selection for Timetabling Problems
Burke, Edmund; Petrovic, Sanja; Qu, Rong
2006-01-01
This paper presents a case-based heuristic selection approach for automated university course and exam timetabling. The method described in this paper is motivated by the goal of developing timetabling systems that are fundamentally more general than the current state of the art. Heuristics that worked well in previous similar situations are memorized in a case base and are retrieved for solving the problem in hand. Knowledge discovery techniques are employed in two distinct scenarios. Firstl...
GYutsis: heuristic based calculation of general recoupling coefficients
Van Dyck, D.; Fack, V.
2003-08-01
General angular momentum recoupling coefficients can be expressed as a summation formula over products of 6- j coefficients. Yutsis, Levinson and Vanagas developed graphical techniques for representing the general recoupling coefficient as a cubic graph and they describe a set of reduction rules allowing a stepwise generation of the corresponding summation formula. This paper is a follow up to [Van Dyck and Fack, Comput. Phys. Comm. 151 (2003) 353-368] where we described a heuristic algorithm based on these techniques. In this article we separate the heuristic from the algorithm and describe some new heuristic approaches which can be plugged into the generic algorithm. We show that these new heuristics lead to good results: in many cases we get a more efficient summation formula than our previous approach, in particular for problems of higher order. In addition the new features and the use of our program GYutsis, which implements these techniques, is described both for end users and application programmers. Program summaryTitle of program: CycleCostAlgorithm, GYutsis Catalogue number: ADSA Program Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSA Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland. Users may obtain the program also by downloading either the compressed tar file gyutsis.tgz (for Unix and Linux) or the zip file gyutsis.zip (for Windows) from our website ( http://caagt.rug.ac.be/yutsis/). An applet version of the program is also available on our website and can be run in a web browser from the URL http://caagt.rug.ac.be/yutsis/GYutsisApplet.html. Licensing provisions: none Computers for which the program is designed: any computer with Sun's Java Runtime Environment 1.4 or higher installed. Programming language used: Java 1.2 (Compiler: Sun's SDK 1.4.0) No. of lines in program: approximately 9400 No. of bytes in distributed program, including test data, etc.: 544 117 Distribution format: tar gzip file Nature of
A new method for thread calibration on coordinate measuring machines
DEFF Research Database (Denmark)
Carmignato, Simone; De Chiffre, Leonardo
2003-01-01
portions with corresponding paths on a calibrated sphere. The feasibility of applying the method to calibrate a parallel thread gauge with respect to all the relevant thread parameters was demonstrated experimentally using a precision CMM. Application of the comparator approach as described in ISO 15530......CIRP Annals – Paper proposal temporary reference: P15. This paper presents a new method for the calibration of thread gauges on coordinate measuring machines. The procedure involves scanning of thread profiles using a needle-like probe, achieving traceability by substitution of different thread......-3 gave measuring uncertainties comparable to the values from usual calibration methods on dedicated equipment, e.g. a measuring uncertainty of 1.5 µm was achieved for measurement of the pitch, and 2-2.5 µm for diameter measurements....
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.
Mathematical models and heuristic solutions for container positioning problems in port terminals
DEFF Research Database (Denmark)
Kallehauge, Louise Sibbesen
2008-01-01
This PhD thesis is concerned with the container positioning problem (CPP) which consists in determining optimal sequences of positions and moves for containers in a single storage block of a terminal yard. The purpose of the thesis is to apply Operations Research (OR) methods for optimizing the CPP...... 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...
Directory of Open Access Journals (Sweden)
Mário Mestria
2014-11-01
Full Text Available In this paper, we propose new heuristic methods for solver the Clustered Traveling Salesman Problem (CTSP. The 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. We develop two Variable Neighborhood Random Descent with Iterated Local for solver the CTSP. The heuristic methods proposed were tested in types of instances with data at different level of granularity for the number of vertices and clusters. The computational results showed that the heuristic methods outperform recent existing methods in the literature and they are competitive with an exact algorithm using the Parallel CPLEX software.
A hop count based heuristic routing protocol for mobile delay tolerant networks.
You, Lei; Li, Jianbo; Wei, Changjiang; Dai, Chenqu; Xu, Jixing; Hu, Lejuan
2014-01-01
Routing in delay tolerant networks (DTNs) is a challenge since it must handle network partitioning, long delays, and dynamic topology. Meanwhile, routing protocols of the traditional mobile ad hoc networks (MANETs) cannot work well due to the failure of its assumption that most network connections are available. In this paper, we propose a hop count based heuristic routing protocol by utilizing the information carried by the peripatetic packets in the network. A heuristic function is defined to help in making the routing decision. We formally define a custom operation for square matrices so as to transform the heuristic value calculation into matrix manipulation. Finally, the performance of our proposed algorithm is evaluated by the simulation results, which show the advantage of such self-adaptive routing protocol in the diverse circumstance of DTNs.
Meta-heuristics in cellular manufacturing: A state-of-the-art review
Directory of Open Access Journals (Sweden)
Tamal Ghosh
2011-01-01
Full Text Available Meta-heuristic approaches are general algorithmic framework, often nature-inspired and designed to solve NP-complete optimization problems in cellular manufacturing systems and has been a growing research area for the past two decades. This paper discusses various meta-heuristic techniques such as evolutionary approach, Ant colony optimization, simulated annealing, Tabu search and other recent approaches, and their applications to the vicinity of group technology/cell formation (GT/CF problem in cellular manufacturing. The nobility of this paper is to incorporate various prevailing issues, open problems of meta-heuristic approaches, its usage, comparison, hybridization and its scope of future research in the aforesaid area.
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.
Azad, Mohammad
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.
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.
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.
Heuristic space diversity management in a meta-hyper-heuristic framework
CSIR Research Space (South Africa)
Grobler, J
2014-07-01
Full Text Available IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 6-11 July 2014 Heuristic Space Diversity Management in a Meta-Hyper- Heuristic Framework Jacomine Grobler1 and Andries P. Engelbrecht2 1Department of Industrial and Systems...
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.
Carbon nanotube and graphene multiple-thread yarns.
Zhong, Xiaohua; Wang, Rui; Yangyang, Wen; Yali, Li
2013-02-07
Carbon nanotubes (CNTs) and graphene (GNS) hybrid multiple-thread yarns were fabricated by chemical vapor deposition followed by a posted-stretching processing. The as-prepared CNTs and GNS multiple-thread yarns consisted of tens of single-thread fibers with diameters of around 20 μm. The single-thread fibers are composed of double-walled carbon nanotube (DWNT) bundles and GNS tablets. DWNT bundles in the single-thread fiber are highly disordered and are rounded by GNS. The content and dimensions of GNS are changeable along the fiber axial direction. The as-obtained CNT and GNS hybrid multiple-thread yarns can be twisted, forming one fiber. The mechanical measurement of the twisted yarn gave a strength of 300 MPa and the electrical conductivity is 10(5) S m(-1). These unique structures, possessing various promising properties, can be readily and directly applied in different fields. Here, the hybrid yarns of CNTs and GNS were applied as a lamp thread and woven macroscopic body, as demonstrated.
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.
Heuristic algorithms for scheduling heat-treatment furnaces of steel ...
Indian Academy of Sciences (India)
treatment furnaces in a steel-casting foundry, a special problem of batch processor scheduling, ... production management is to maximize throughput and reduce flow time and WIP. This motivated the choice of ..... A computational experiment is appropriate in order to provide a perspective on the relative effectiveness of any ...
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
Two phase heuristic algorithm for the university course timetabling
African Journals Online (AJOL)
Mgina
AR Mushi. Department of Mathematics, Box 35062, University of Dar es salaam, Tanzania ... framework is difficult. In general, articles describing solution procedures can easily be found but few discuss the actual implementation of a practical problem. Some of these .... Note that it is not necessary to check for feasibility when ...
Heuristic algorithms for scheduling heat-treatment furnaces of steel ...
Indian Academy of Sciences (India)
The scheduling of furnaces for heat-treatment of castings is of considerable interest as a large proportion of the total production time is the processing times of these ... Department of Management Studies, Indian Institute of Science, Bangalore 560 012; Singapore-MIT Alliance, School of Mechanical and Aerospace ...
Parameterized Algorithmics for Graph Modification Problems: On Interactions with Heuristics
Komusiewicz, Christian; Nichterlein, André; Niedermeier, Rolf
2016-01-01
In graph modification problems, one is given a graph G and the goal is to apply a minimum number of modification operations (such as edge deletions) to G such that the resulting graph fulfills a certain property. For example, the Cluster Deletion problem asks to delete as few edges as possible such that the resulting graph is a disjoint union of cliques. Graph modification problems appear in numerous applications, including the analysis of biological and social networks. Typically, graph modi...
Two Phase Heuristic Algorithm for the University Course Timetabling ...
African Journals Online (AJOL)
University course timetabling is the problem of scheduling resources such as lecturers, courses, and rooms to a number of timeslots over a planning horizon, normally a week, while satisfying a number of problem-specific constraints. Since timetabling problems differ from one institution to another, this paper investigated the ...
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.
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...... 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...
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.
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
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.
Finding Solutions to Sudoku Puzzles Using Human Intuitive Heuristics
Directory of Open Access Journals (Sweden)
Nelishia Pillay
2012-09-01
Full Text Available Sudoku is a logical puzzle that has achieved international popularity. Given this, there have been a number of computer solvers developed for this puzzle. Various methods including genetic algorithms, simulated annealing, particle swarm optimization and harmony search have been evaluated for this purpose. The approach described in this paper combines human intuition and optimization to solve Sudoku problems. The main contribution of this paper is a set of heuristic moves, incorporating human expertise, to solve Sudoku puzzles. The paper investigates the use of genetic programming to optimize a space of programs composed of these heuristics moves, with the aim of evolving a program that can produce a solution to the Sudoku problem instance. Each program is a combination of randomly selected moves. The approach was tested on 1800 Sudoku puzzles of differing difficulty. The approach presented was able to solve all 1800 problems, with a majority of these problems being solved in under a second. For a majority of the puzzles evolution was not needed and random combinations of the moves created during the initial population produced solutions. For the more difficult problems at least one generation of evolution was needed to find a solution. Further analysis revealed that solution programs for the more difficult problems could be found by enumerating random combinations of the move operators, however at a cost of higher runtimes. The performance of the approach presented was found to be comparable to other methods used to solve Sudoku problems and in a number of cases produced better results.
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.
Heuristic optimization of the scanning path of particle therapy beams
Energy Technology Data Exchange (ETDEWEB)
Pardo, J.; Donetti, M.; Bourhaleb, F.; Ansarinejad, A.; Attili, A.; Cirio, R.; Garella, M. A.; Giordanengo, S.; Givehchi, N.; La Rosa, A.; Marchetto, F.; Monaco, V.; Pecka, A.; Peroni, C.; Russo, G.; Sacchi, R. [Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy) and Fondazione CNAO, Via Caminadella 16, I-20123, Milano (Italy); Dipartimento di Fisica Sperimentale, Universita di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy) and Dipartimento di Fisica Sperimentale, Universita di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy) and Dipartimento di Fisica Sperimentale, Universita di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy) and Dipartimento di Fisica Sperimentale, Universita di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Via P. Giuria 1, I-10125 Torino (Italy) and Dipartimento di Fisica Sperimentale, Universita di Torino, Via P. Giuria 1, I-10125 Torino (Italy)
2009-06-15
Quasidiscrete scanning is a delivery strategy for proton and ion beam therapy in which the beam is turned off when a slice is finished and a new energy must be set but not during the scanning between consecutive spots. Different scanning paths lead to different dose distributions due to the contribution of the unintended transit dose between spots. In this work an algorithm to optimize the scanning path for quasidiscrete scanned beams is presented. The classical simulated annealing algorithm is used. It is a heuristic algorithm frequently used in combinatorial optimization problems, which allows us to obtain nearly optimal solutions in acceptable running times. A study focused on the best choice of operational parameters on which the algorithm performance depends is presented. The convergence properties of the algorithm have been further improved by using the next-neighbor algorithm to generate the starting paths. Scanning paths for two clinical treatments have been optimized. The optimized paths are found to be shorter than the back-and-forth, top-to-bottom (zigzag) paths generally provided by the treatment planning systems. The gamma method has been applied to quantify the improvement achieved on the dose distribution. Results show a reduction of the transit dose when the optimized paths are used. The benefit is clear especially when the fluence per spot is low, as in the case of repainting. The minimization of the transit dose can potentially allow the use of higher beam intensities, thus decreasing the treatment time. The algorithm implemented for this work can optimize efficiently the scanning path of quasidiscrete scanned particle beams. Optimized scanning paths decrease the transit dose and lead to better dose distributions.
Impact tolerance in mussel thread networks by heterogeneous material distribution
Qin, Zhao; Buehler, Markus J.
2013-07-01
The Mytilidae, generally known as marine mussels, are known to attach to most substrates including stone, wood, concrete and iron by using a network of byssus threads. Mussels are subjected to severe mechanical impacts caused by waves. However, how the network of byssus threads keeps the mussel attached in this challenging mechanical environment is puzzling, as the dynamical forces far exceed the measured strength of byssus threads and their attachment to the environment. Here we combine experiment and simulation, and show that the heterogeneous material distribution in byssus threads has a critical role in decreasing the effect of impact loading. We find that a combination of stiff and soft materials at an 80:20 ratio enables mussels to rapidly and effectively dissipate impact energy. Notably, this facilitates a significantly enhanced strength under dynamical loading over 900% that of the strength under static loading.
A multi-threading approach to secure VERIFYPIN
CSIR Research Space (South Africa)
Frieslaar, Ibraheem
2016-10-01
Full Text Available This research investigates the use of a multi-threaded framework as a software countermeasure mechanism to prevent attacks on the verifypin process in a pin-acceptance program. The implementation comprises of using various mathematical operations...
Saeed, Fahad; Hoffert, Jason D; Pisitkun, Trairak; Knepper, Mark A
2014-04-01
Modern mass spectrometers can produce large numbers of peptide spectra from complex biological samples in a short time. A substantial amount of redundancy is observed in these data sets from peptides that may get selected multiple times in Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) experiments. A large number of spectra do not get mapped to specific peptide sequences due to low signal-to-noise (S/N) ratio of the spectra from these machines. Clustering is one way to mitigate the problems of these complex mass spectrometry data sets. Recently we presented a graph theoretic framework, known as CAMS, for clustering of large-scale mass spectrometry data. CAMS utilized a novel metric to exploit the spatial patterns in the mass spectrometry peaks which allowed highly accurate clustering results. However, comparison of each spectrum with every other spectrum makes the clustering problem computationally inefficient. In this paper we present a parallel algorithm, called P-CAMS, that uses thread-level and instruction-level parallelism on multicore architectures to substantially decrease running times. P-CAMS relies on intelligent matrix completion to reduce the number of comparisons, threads to run on each core and Single Instruction Multiple Data (SIMD) paradigm inside each thread to exploit massive parallelism on multicore architectures. A carefully crafted load-balanced scheme that uses spatial locations of the mass spectrometry peaks mapped to nearest level cache and core allows super-linear speedups. We study the scalability of the algorithm with a wide variety of mass spectrometry data and variation in architecture specific parameters. The results show that SIMD style data parallelism combined with thread-level parallelism for multicore architectures is a powerful combination that allows substantial reduction in runtimes even for all-to-all comparison algorithms. The quality assessment is performed using real-world data set and is shown to be consistent
Age Effects and Heuristics in Decision Making*
Besedeš, Tibor; Deck, Cary; Sarangi, Sudipta; Shor, Mikhael
2011-01-01
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. PMID:22544977
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.
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 Drift Elimination for Personnel Tracking Systems
Borenstein, Johann; Ojeda, Lauro
This paper pertains to the reduction of the effects of measurement errors in rate gyros used for tracking, recording, or monitoring the position of persons walking indoors. In such applications, bias drift and other gyro errors can degrade accuracy within minutes. To overcome this problem we developed the Heuristic Drift Elimination (HDE) method, that effectively corrects bias drift and other slow-changing errors. HDE works by making assumptions about walking in structured, indoor environments. The paper explains the heuristic assumptions and the HDE method, and shows experimental results. In typical applications, HDE maintains near-zero heading errors in walks of unlimited duration.
Attenuation of the tip vortex flow using a flexible thread
Lee, Seung-Jae; Shin, Jin-Woo; Arndt, Roger E. A.; Suh, Jung-Chun
2018-01-01
Tip vortex cavitation (TVC) is important in a number of practical engineering applications. The onset of TVC is a critical concern for navy surface ships and submarines that aim to increase their capability to evade detection. A flexible thread attachment at blade tips was recently suggested as a new method to delay the onset of TVC. Although the occurrence of TVC can be reduced using a flexible thread, no scientific investigation focusing on its mechanisms has been undertaken. Thus, herein, we experimentally investigated the use of the flexible thread to suppress TVC from an elliptical wing. These investigations were performed in a cavitation tunnel and involved an observation of TVC using high-speed cameras, motion tracking of the thread using image-processing techniques, and near-field flow measurements performed using stereoscopic particle image velocimetry. The experimental data suggested that the flexible thread affects the axial velocity field more than the circumferential velocity field around the TVC axis. Furthermore, we observed no clear dependence of the vortex core size, circulation, and flow unsteadiness on TVC suppression. However, the presence of the thread at the wing tip led to a notable reduction in the streamwise velocity field, thereby alleviating TVC.
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.
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.
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
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.
Local search-based heuristics for the multiobjective multidimensional knapsack problem
Directory of Open Access Journals (Sweden)
Dalessandro Soares Vianna
2012-01-01
Full Text Available In real optimization problems it is generally desirable to optimize more than one performance criterion (or objective at the same time. The goal of the multiobjective combinatorial optimization (MOCO is to optimize simultaneously r > 1 objectives. As in the single-objective case, the use of heuristic/metaheuristic techniques seems to be the most promising approach to MOCO problems because of their efficiency, generality and relative simplicity of implementation. In this work, we develop algorithms based on Greedy Randomized Adaptive Search Procedure (GRASP and Iterated Local Search (ILS metaheuristics for the multiobjective knapsack problem. Computational experiments on benchmark instances show that the proposed algorithms are very robust and outperform other heuristics in terms of solution quality and running times.
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...
Heuristic reusable dynamic programming: efficient updates of local sequence alignment.
Hong, Changjin; Tewfik, Ahmed H
2009-01-01
Recomputation of the previously evaluated similarity results between biological sequences becomes inevitable when researchers realize errors in their sequenced data or when the researchers have to compare nearly similar sequences, e.g., in a family of proteins. We present an efficient scheme for updating local sequence alignments with an affine gap model. In principle, using the previous matching result between two amino acid sequences, we perform a forward-backward alignment to generate heuristic searching bands which are bounded by a set of suboptimal paths. Given a correctly updated sequence, we initially predict a new score of the alignment path for each contour to select the best candidates among them. Then, we run the Smith-Waterman algorithm in this confined space. Furthermore, our heuristic alignment for an updated sequence shows that it can be further accelerated by using reusable dynamic programming (rDP), our prior work. In this study, we successfully validate "relative node tolerance bound" (RNTB) in the pruned searching space. Furthermore, we improve the computational performance by quantifying the successful RNTB tolerance probability and switch to rDP on perturbation-resilient columns only. In our searching space derived by a threshold value of 90 percent of the optimal alignment score, we find that 98.3 percent of contours contain correctly updated paths. We also find that our method consumes only 25.36 percent of the runtime cost of sparse dynamic programming (sDP) method, and to only 2.55 percent of that of a normal dynamic programming with the Smith-Waterman algorithm.
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.
Coiling and maturation of a high-performance fibre in hagfish slime gland thread cells
Winegard, Timothy; Herr, Julia; Mena, Carlos; Lee, Betty; Dinov, Ivo; Bird, Deborah; Bernards, Mark; Hobel, Sam; van Valkenburgh, Blaire; Toga, Arthur; Fudge, Douglas
2014-04-01
The defensive slime of hagfishes contains thousands of intermediate filament protein threads that are manufactured within specialized gland thread cells. The material properties of these threads rival those of spider dragline silks, which makes them an ideal model for biomimetic efforts to produce sustainable protein materials, yet how the thread is produced and organized within the cell is not well understood. Here we show how changes in nuclear morphology, size and position can explain the three-dimensional pattern of thread coiling in gland thread cells, and how the ultrastructure of the thread changes as very young thread cells develop into large cells with fully mature coiled threads. Our model provides an explanation for the complex process of thread assembly and organization that has fascinated and perplexed biologists for over a century, and provides valuable insights for the quest to manufacture high-performance biomimetic protein materials.
A rescheduling heuristic for the single machine total tardiness problem
African Journals Online (AJOL)
In this paper, we propose a rescheduling heuristic for scheduling N jobs on a single machine in order to minimise total tardiness. The heuristic is of the interchange type and constructs a schedule from the modified due date (MDD) schedule. Unlike most interchange heuristics that consider interchanges involving only two ...
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…
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…
Usage of Major Heuristics in Property Investment Valuation in Nigeria
African Journals Online (AJOL)
Toshiba
effect of heuristics, but concluded that experience and feedback should mitigate much bias. Tversky and Kahnemann (1974) identified three types of heuristics: representative; availability and anchoring and adjustment. Evans. (1989) later added a fourth: positivity (other lesser heuristics have subsequently been identified).
Routing Post-Disaster Traffic Floods Heuristics
Nasralla, ZHA; Musa, MOI; El-Gorashi, TEH; Elmirghani, JMH
2016-01-01
In this paper, we present three heuristics for mitigating post-disaster traffic floods. First exploiting the excess capacity, second rerouting backup paths, finally redistributing the whole traffic by rerouting the working and protection paths to accommodate more floods. Using these mitigation approaches can reduce the blocking by up to 30%.
A Heuristic Bioinspired for 8-Piece Puzzle
Machado, M. O.; Fabres, P. A.; Melo, J. C. L.
2017-10-01
This paper investigates a mathematical model inspired by nature, and presents a Meta-Heuristic that is efficient in improving the performance of an informed search, when using strategy A * using a General Search Tree as data structure. The work hypothesis suggests that the investigated meta-heuristic is optimal in nature and may be promising in minimizing the computational resources required by an objective-based agent in solving high computational complexity problems (n-part puzzle) as well as In the optimization of objective functions for local search agents. The objective of this work is to describe qualitatively the characteristics and properties of the mathematical model investigated, correlating the main concepts of the A * function with the significant variables of the metaheuristic used. The article shows that the amount of memory required to perform this search when using the metaheuristic is less than using the A * function to evaluate the nodes of a general search tree for the eight-piece puzzle. It is concluded that the meta-heuristic must be parameterized according to the chosen heuristic and the level of the tree that contains the possible solutions to the chosen problem.
Sensitivity Analysis of List Scheduling Heuristics
A.W.J. Kolen; A.H.G. Rinnooy Kan (Alexander); C.P.M. van Hoesel; A.P.M. Wagelmans (Albert)
1994-01-01
textabstractWhen jobs have to be processed on a set of identical parallel machines so as to minimize the makespan of the schedule, list scheduling rules form a popular class of heuristics. The order in which jobs appear on the list is assumed here to be determined by the relative size of their
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…
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...
Bayesian networks: a combined tuning heuristic
Bolt, J.H.
2016-01-01
One of the issues in tuning an output probability of a Bayesian network by changing multiple parameters is the relative amount of the individual parameter changes. In an existing heuristic parameters are tied such that their changes induce locally a maximal change of the tuned probability. This
Heuristics for Knowledge Acquisition from Maps.
Thorndyke, Perry W.
This paper investigates how people acquire knowledge from maps. Emphasis is placed on heuristics--defined as the procedures that people use to select, combine, and encode map information in memory. The objective is to develop a theory of expertise in map learning by analyzing differences between fast and slow learners in terms of differences in…
Thread milling on N/C and CNC milling machines. Final report
Energy Technology Data Exchange (ETDEWEB)
Ashbaugh, F.A.; Murry, K.R.
1985-12-01
A unique thread-cutting tool design has been developed which permits threading of internal or external features; right- or left-hand threads; and standard, metric, or special pitches within a given size range without changing tools. One of the major advantages of the technique is the ability to produce small threads on N/C and CNC milling manchines. This study presents results showing fabrication of quality threads as small as number 0-80 in selected materials.
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.
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.
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.
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.
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…
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.
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.
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.
Regimes of miscible fluid thread formation in microfluidic focusing sections
Cubaud, Thomas; Notaro, Sara
2014-12-01
We experimentally study the formation and stability of miscible fluid threads made of high-viscosity liquids using hydrodynamic focusing sections. Miscible core annular flows are useful for transporting viscous materials and can be destabilized for enhancing mass transfer. We delineate phase-diagrams of the generation of lubricated threads from low to large viscosity contrasts with various diffusion coefficients. Depending on fluid properties and flow rates of injection, stable microflows are classified into engulfment, thread, and tubing regimes. For low Péclet numbers, we examine thread dynamics when diffusive effects strongly alter basic flow structures and induce new flow configurations, including ultra-diffusive and diffusive instability regimes. Another unstable flow arrangement is investigated for moderate Reynolds numbers where small threads are rapidly destabilized in the inertial flow field of the sheath fluid near the fluid junction. This study provides an overview of stable and unstable flow regimes and their transitions during the formation of miscible viscous fluid filaments in square microchannels.
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.
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
2011-01-01
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 convergence. These
CNT coated thread micro-electro-mechanical system for finger proprioception sensing
Shafi, A. A.; Wicaksono, D. H. B.
2017-04-01
In this paper, we aim to fabricate cotton thread based sensor for proprioceptive application. Cotton threads are utilized as the structural component of flexible sensors. The thread is coated with multi-walled carbon nanotube (MWCNT) dispersion by using facile conventional dipping-drying method. The electrical characterization of the coated thread found that the resistance per meter of the coated thread decreased with increasing the number of dipping. The CNT coated thread sensor works based on piezoresistive theory in which the resistance of the coated thread changes when force is applied. This thread sensor is sewed on glove at the index finger between middle and proximal phalanx parts and the resistance change is measured upon grasping mechanism. The thread based microelectromechanical system (MEMS) enables the flexible sensor to easily fit perfectly on the finger joint and gives reliable response as proprioceptive sensing.
Lifting the Lower Face With an Absorbable Polydioxanone (PDO) Thread.
Karimi, Kian; Reivitis, Alexandra
2017-09-01
Traditional rejuvenation techniques include chemical peels, rhytidectomy of the skin, laser resurfacing, injection of dermal fillers and neurotoxins, and invasive surgical procedures. Patients with brow ptosis, jowl formation, and deepening nasolabial folds currently seek antiaging procedures with no incisions and minimal downtime such as thread-lifting with barbed sutures. The present report describes a case in which polydioxanone threads were used to lift the lower third of a patient's face. Fillers were used to supplement the results achieved by the thread lift because often, when tissue has been lifted, volume deficits are revealed, which can be corrected with dermal fillers. The procedure was performed in less than 30 minutes and was well tolerated. Mild swelling at the insertion points and general treatment area resolved within 7 days without intervention. Bruising was not observed. The patient showed remarkable improvement 7 months after the procedure. J Drugs Dermatol. 2017;16(9):932-934..
Experiments in Aligning Threaded Parts Using a Robot Hand
Diftler, M. A.; Walker, I. D.
1999-01-01
Techniques for determining and correcting threaded part alignment using force and angular position data are developed to augment currently limited techniques for align- ing threaded parts. These new techniques are based on backspinning a nut with respect to a bolt and measuring the force change that occurs when the bolt "falls" into the nut. Kinematic models that describe the relationship between threaded parts during backspinning are introduced and are used to show how angular alignment may be determined. The models indicate how to distinguish between the aligned and misaligned cases of a bolt and a nut connection by using axial force data only. In addition, by tracking the in-plane relative attitude of the bolt during spinning, data can be obtained on the direction of the angular misalignment which, in turn, is used to correct the misalignment. Results from experiments using a bolt held in a specialized fixture and a three fingers Stanford/JPL hand are presented.
Weaving of organic threads into a crystalline covalent organic framework.
Liu, Yuzhong; Ma, Yanhang; Zhao, Yingbo; Sun, Xixi; Gándara, Felipe; Furukawa, Hiroyasu; Liu, Zheng; Zhu, Hanyu; Zhu, Chenhui; Suenaga, Kazutomo; Oleynikov, Peter; Alshammari, Ahmad S; Zhang, Xiang; Terasaki, Osamu; Yaghi, Omar M
2016-01-22
A three-dimensional covalent organic framework (COF-505) constructed from helical organic threads, designed to be mutually weaving at regular intervals, has been synthesized by imine condensation reactions of aldehyde functionalized copper(I)-bisphenanthroline tetrafluoroborate, Cu(PDB)2(BF4), and benzidine (BZ). The copper centers are topologically independent of the weaving within the COF structure and serve as templates for bringing the threads into a woven pattern rather than the more commonly observed parallel arrangement. The copper(I) ions can be reversibly removed and added without loss of the COF structure, for which a tenfold increase in elasticity accompanies its demetalation. The threads in COF-505 have many degrees of freedom for enormous deviations to take place between them, throughout the material, without undoing the weaving of the overall structure. Copyright © 2016, American Association for the Advancement of Science.
Evaluating the multi-threading countermeasure
CSIR Research Space (South Africa)
Frieslaar, Ibraheem
2016-12-01
Full Text Available circuit board (PCB) and the device used to capture the data is the ChipWhisperer. Figure 5 depicts the hardware configuration as the ChipWhisperer is connected to the PCB via a serial cable, a low noise amplifier is connected to the ChipWhisperer which... on their implementation with minimal samples. Therefore, this research performs both the CPA and template attacks. Furthermore, the research applies additional processing techniques such as the elastic alignment and low pass filtering algorithms to enhance the attacks...
Addressing Authorship Issues Prospectively: A Heuristic Approach.
Roberts, Laura Weiss
2017-02-01
Collaborative writing in academic medicine gives rise to more richly informed scholarship, and yet challenging ethical issues surrounding authorship are commonly encountered. International guidelines on authorship help clarify whether individuals who have contributed to a completed scholarly work have been correctly included as authors, but these guidelines do not facilitate intentional and proactive authorship planning or decisions regarding authorship order.In this Commentary, the author presents a heuristic approach to help collaborators clarify, anticipate, and resolve practical and ethically important authorship issues as they engage in the process of developing manuscripts. As this approach illustrates, assignment of authorship should balance work effort and professional responsibility, reflecting the effort and intellectual contribution and the public accountability of the individuals who participate in the work. Using a heuristic approach for managing authorship issues prospectively can foster an ethical, collaborative writing process in which individuals are properly recognized for their contributions.
High-Level Multi-Threading in hProlog
Van Overveldt, Timon; Demoen, Bart
2011-01-01
A new high-level interface to multi-threading in Prolog, implemented in hProlog, is described. Modern CPUs often contain multiple cores and through high-level multi-threading a programmer can leverage this power without having to worry about low-level details. Two common types of high-level explicit parallelism are discussed: independent and-parallelism and competitive or-parallelism. A new type of explicit parallelism, pipeline parallelism, is proposed. This new type can be used in certain c...
Heuristics and Biases in Military Decision Making
2010-10-01
critical com- ponents increases, we find mathematically that the probability of event (or system) failure increases. However, we again find that...Uncertainty: Heuristics and Biases, ed. Daniel Kahneman and Amos Tversky (New York, Cambridge University Press, 1982), 156-57. It is similar to a quiz I...gave during my Game Theory class at West Point. 38. Mathematically , this problem can be solved using Bayesian inference. 39. Some may feel that the
Empirical heuristics for improving Intermittent Demand Forecasting
Petropoulos, Fotios; Nikolopoulos, Konstantinos; Spithourakis, George; Assimakopoulos, Vassilios
2013-01-01
Purpose– Intermittent demand appears sporadically, with some time periods not even displaying any demand at all. Even so, such patterns constitute considerable proportions of the total stock in many industrial settings. Forecasting intermittent demand is a rather difficult task but of critical importance for corresponding cost savings. The current study aims to examine the empirical outcomes of three heuristics towards the modification of established intermittent demand forecasting approaches...
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.
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 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.
Antenna Design by Means of the Fruit Fly Optimization Algorithm
Directory of Open Access Journals (Sweden)
Lucas Polo-López
2018-01-01
Full Text Available In this work a heuristic optimization algorithm known as the Fruit fly Optimization Algorithm is applied to antenna design problems. The original formulation of the algorithm is presented and it is adapted to array factor and horn antenna optimization problems. Specifically, it is applied to the array factor synthesis of uniformly-fed, non-equispaced arrays and to the profile optimization of multimode horn antennas. Several numerical examples are presented and the obtained results are compared with those provided by a deterministic optimization based on a simplex method and another well-known heuristic approach, the Genetic Algorithm.
Combination of Chaotic Neurodynamics with the 2-opt Algorithm to Solve Traveling Salesman Problems
Hasegawa, M.; Ikeguchi, T.; Aihara, K.
1997-09-01
We propose a novel approach for combinatorial optimization problems. For solving the traveling salesman problems, we combine chaotic neurodynamics with heuristic algorithm. We select the heuristic algorithm of 2-opt as a basic part, because it is well understood that this simple algorithm is very effective for the traveling salesman problems. Although the conventional approaches with chaotic neurodynamics were only applied to such very small problems as 10 cities, our method exhibits higher performance for larger size problems with the order of 102.
Heuristic Scheme for Home Circuit Grouping andWavelength Assignment in LOBS-HC Networks
Yang, Ximin; Yi, Bo; Tang, Wan; Li, Jingcong
2014-09-01
Grouping the Home Circuits (HCs) with the same source is a critical issue of Labeled Optical Burst Switching with Home Circuit (LOBS-HC). To maximize the wavelength utilization in LOBS-HC ring networks, an HC grouping and wavelength assignment scheme, called Longest Path Matching and Graph Coloring (LPMGC), is proposed. LPMGC consists of two phases: grouping and wavelength assignment. First, a heuristic algorithm, named Longest Path Matching (LPM), is proposed to group the HCs according to the longest common path matching between HCs and to make each group as large as possible. And then, Graph Coloring (GC) is introduced to assign wavelengths for HC groups. The numerical results show that the proposed scheme performances better than Complementary HC Assignment (CHA) and some other heuristics in both unidirectional and bidirectional LOBS-HC ring networks in terms of wavelength utilization.
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. }}
The Automated Threaded Fastening Based on On-line Identification
Directory of Open Access Journals (Sweden)
Mongkorn Klingajay
2004-12-01
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.
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.
Comparative clinical assessment of cotton hair thread and silk ...
African Journals Online (AJOL)
The gross tissue reactivity, bacterial load counts and clinical parameters were investigated following the use of cotton hair thread (CHT) and silk suture on surgically induced wounds on rabbits. Twelve clinically healthy male rabbits of New Zealand breed were used. They were acclimatized for two weeks and randomly ...
Usefulness of Gold Thread Implantation for Crow’s
Directory of Open Access Journals (Sweden)
Woo Seob Kim
2012-01-01
Full Text Available Background Conservative techniques designed to block or delay the aging process have beenutilized in various ways for many years. However, their effects can be relatively minimal andshort-term in most cases compared to surgery. The objective of this study was to evaluate theefficacy and safety of gold thread implantation for the treatment of periorbital wrinkles.Methods A total of 78 consecutive patients who showed mild to severe periorbital wrinkleswere deemed appropriate candidates, including 69 women and 9 men ranging from 31 to 59years (mean, 47 years. Six gold threads about 4 cm in length were inserted subdermally ineach patient at intervals of about 0.5 cm. Follow-up assessments were performed 1, 4, and 12weeks after the procedure. The efficacy was rated by the physician using the Wrinkle SeverityRating Scale and patients who made global assessments of changes in periorbital wrinklesusing the Visual Analog Scale. Adverse events were monitored throughout the course of thestudy.Results The patients showed significant improvements after the procedure. There were minorcomplications such as foreign body sensation in the eye (2.63% and eye pain (1.32% thatimproved spontaneously without any specific treatments.Conclusions Subdermal implantation of gold thread improves the appearance of periorbitalwrinkles and does not appear to have serious side effects. Insertion of gold thread may be aneffective and safe method for facial rejuvenation.
Usefulness of Gold Thread Implantation for Crow's Feet
Directory of Open Access Journals (Sweden)
Kee Cheol Shin
2012-01-01
Full Text Available BackgroundConservative techniques designed to block or delay the aging process have been utilized in various ways for many years. However, their effects can be relatively minimal and short-term in most cases compared to surgery. The objective of this study was to evaluate the efficacy and safety of gold thread implantation for the treatment of periorbital wrinkles.MethodsA total of 78 consecutive patients who showed mild to severe periorbital wrinkles were deemed appropriate candidates, including 69 women and 9 men ranging from 31 to 59 years (mean, 47 years. Six gold threads about 4 cm in length were inserted subdermally in each patient at intervals of about 0.5 cm. Follow-up assessments were performed 1, 4, and 12 weeks after the procedure. The efficacy was rated by the physician using the Wrinkle Severity Rating Scale and patients who made global assessments of changes in periorbital wrinkles using the Visual Analog Scale. Adverse events were monitored throughout the course of the study.ResultsThe patients showed significant improvements after the procedure. There were minor complications such as foreign body sensation in the eye (2.63% and eye pain (1.32% that improved spontaneously without any specific treatments.ConclusionsSubdermal implantation of gold thread improves the appearance of periorbital wrinkles and does not appear to have serious side effects. Insertion of gold thread may be an effective and safe method for facial rejuvenation.
From Primary to Secondary Science: Keeping the Threads Intact
Mould, Kirsten
2015-01-01
There are many transition points in the school life of a child, but the move from primary to secondary school is a particularly significant one. How can both the social and academic threads remain intact? In this article, Kristen Mould discusses the main issues relating to transition from primary to secondary science. She cites the primary factors…
Quantitative Security Analysis for Multi-threaded Programs
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Tri Minh Ngo
2013-06-01
Full Text Available Quantitative theories of information flow give us an approach to relax the absolute confidentiality properties that are difficult to satisfy for many practical programs. The classical information-theoretic approaches for sequential programs, where the program is modeled as a communication channel with only input and output, and the measure of leakage is based on the notions of initial uncertainty and remaining uncertainty after observing the final outcomes, are not suitable to multi-threaded programs. Besides, the information-theoretic approaches have been also shown to conflict with each other when comparing programs. Reasoning about the exposed information flow of multi-threaded programs is more complicated, since the outcomes of such programs depend on the scheduler policy, and the leakages in intermediate states also contribute to the overall leakage of the program. This paper proposes a novel model of quantitative analysis for multi-threaded programs that also takes into account the effect of observables in intermediate states along the trace. We define a notion of the leakage of a program trace. Given the fact that the execution of a multi-threaded program is typically described by a set of traces, the leakage of a program under a specific scheduler is computed as the expected value of the leakages of all possible traces. Examples are given to compare our approach with the existing approaches.
Structural Analysis of Taper-Threaded Rebar Couplers
Energy Technology Data Exchange (ETDEWEB)
Chu, Seok Jae [Univ. of Ulsan, Ulsan (Korea, Republic of); Kwon, Hyuk Mo; Seo, Sang Hwan [Sammi Precision Co. Ltd., Ulsan (Korea, Republic of)
2014-05-15
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{sup 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.
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 space diversity management in a meta-hyper-heuristic framework
CSIR Research Space (South Africa)
Grobler, J
2014-07-01
Full Text Available stream_source_info Grobler1_2014.pdf.txt stream_content_type text/plain stream_size 35657 Content-Encoding UTF-8 stream_name Grobler1_2014.pdf.txt Content-Type text/plain; charset=UTF-8 Heuristic Space Diversity... Management in a Meta-Hyper-Heuristic Framework Jacomine Grobler1 and Andries P. Engelbrecht2 1Department of Industrial and Systems Engineering University of Pretoria and Council for Scientific and Industrial Research Email: jacomine.grobler@gmail.com 2...
Brusco, Michael; Stolze, Hannah J; Hoffman, Michaela; Steinley, Douglas
2017-01-01
A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In this paper, we present a computationally efficient simulated annealing algorithm for maximum correlation core/periphery partitioning of binary networks. The algorithm is evaluated using simulated networks consisting of up to 2000 actors and spanning a variety of densities for the intra-core, intra-periphery, and inter-core-periphery components of the network. Core/periphery analyses of problem solving, trust, and information sharing networks for the frontline employees and managers of a consumer packaged goods manufacturer are provided to illustrate the use of the model.
Xu, Huafeng; Agrafiotis, Dimitris K
2003-01-01
We present a new algorithm for nearest neighbor search in general metric spaces. The algorithm organizes the database into recursively partitioned Voronoi regions and represents these partitions in a tree. The separations between the Voronoi regions as well as the radius of each region are used with triangular inequality to derive the minimum possible distance between any point in a region and the query and to discard the region from further search if a smaller distance has already been found. The algorithm also orders the search sequence of the tree branches using the estimate of the minimum possible distance. This simple heuristic proves to considerably enhance the pruning of the search tree. The efficiency of the algorithm is demonstrated on several artificial data sets and real problems in computational chemistry.
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.
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...... of a project crisis is often difficult. Yet, to allow fast crisis response, timely identification is critical for successful crisis management. Adaptive heuristics are judgement strategies that can strive in circumstances of limited and ambiguous information. This article presents a theoretical proposition...... 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...
Parallelization strategies for continuum-generalized method of moments on the multi-thread systems
Bustamam, A.; Handhika, T.; Ernastuti, Kerami, D.
2017-07-01
Continuum-Generalized Method of Moments (C-GMM) covers the Generalized Method of Moments (GMM) shortfall which is not as efficient as Maximum Likelihood estimator by using the continuum set of moment conditions in a GMM framework. However, this computation would take a very long time since optimizing regularization parameter. Unfortunately, these calculations are processed sequentially whereas in fact all modern computers are now supported by hierarchical memory systems and hyperthreading technology, which allowing for parallel computing. This paper aims to speed up the calculation process of C-GMM by designing a parallel algorithm for C-GMM on the multi-thread systems. First, parallel regions are detected for the original C-GMM algorithm. There are two parallel regions in the original C-GMM algorithm, that are contributed significantly to the reduction of computational time: the outer-loop and the inner-loop. Furthermore, this parallel algorithm will be implemented with standard shared-memory application programming interface, i.e. Open Multi-Processing (OpenMP). The experiment shows that the outer-loop parallelization is the best strategy for any number of observations.
Algorithms and Algorithmic Languages.
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Intelligent perturbation algorithms for space scheduling optimization
Kurtzman, Clifford R.
1991-01-01
Intelligent perturbation algorithms for space scheduling optimization are presented in the form of the viewgraphs. The following subject areas are covered: optimization of planning, scheduling, and manifesting; searching a discrete configuration space; heuristic algorithms used for optimization; use of heuristic methods on a sample scheduling problem; intelligent perturbation algorithms are iterative refinement techniques; properties of a good iterative search operator; dispatching examples of intelligent perturbation algorithm and perturbation operator attributes; scheduling implementations using intelligent perturbation algorithms; major advances in scheduling capabilities; the prototype ISF (industrial Space Facility) experiment scheduler; optimized schedule (max revenue); multi-variable optimization; Space Station design reference mission scheduling; ISF-TDRSS command scheduling demonstration; and example task - communications check.
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...
Why less can be more: A Bayesian framework for heuristics
Parpart, Paula
2017-01-01
When making decisions under uncertainty, one common view is that people rely on simple heuristics that deliberately ignore information. One of the greatest puzzles in cognitive science concerns why heuristics can sometimes outperform full-information models, such as linear regression, which make full use of the available information. In this thesis, I will contribute the novel idea that heuristics can be thought of as embodying extreme Bayesian priors. Thereby, an explanation for less-is-more...
Discovery of IPV6 Router Interface Addresses via Heuristic Methods
2015-09-01
NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS DISCOVERY OF IPV6 ROUTER INTERFACE ADDRESSES VIA HEURISTIC METHODS by Matthew D. Gray September...AND SUBTITLE DISCOVERY OF IPV6 ROUTER INTERFACE ADDRESSES VIA HEURISTIC METHODS 5. FUNDING NUMBERS CNS-1111445 6. AUTHOR(S) Matthew D. Gray 7...focuses on IPv6 router infrastructure and examines the possibility of using heuristic methods in order to discover IPv6 router interfaces. We consider two
Design and research on non-standard trapezoidal internal threading insert
Dengzhou, Hu; Wang, Jinge; An, Lingzhi
2017-06-01
In order to improve the machining efficiency of non-standard trapezoidal internal thread of high-temperature alloy Monel K50 material, designed a kind of trapezoidal internal threading insert with strong targeting, used UG software establish 3D model of the insert, Vericut simulation checked the correctness of the threading size and shape, AdvantEdge simulation checked the cutting performance of different cutting tool materials, and finally obtained a non-standard trapezoidal internal threading insert with various excellent performance.
A Graph Search Heuristic for Shortest Distance Paths
Energy Technology Data Exchange (ETDEWEB)
Chow, E
2005-03-24
This paper presents a heuristic for guiding A* search for finding the shortest distance path between two vertices in a connected, undirected, and explicitly stored graph. The heuristic requires a small amount of data to be stored at each vertex. The heuristic has application to quickly detecting relationships between two vertices in a large information or knowledge network. We compare the performance of this heuristic with breadth-first search on graphs with various topological properties. The results show that one or more orders of magnitude improvement in the number of vertices expanded is possible for large graphs, including Poisson random graphs.
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.
An extension for dynamic lot-sizing heuristics
Directory of Open Access Journals (Sweden)
Fabian G. Beck
2015-01-01
Full Text Available This paper presents an efficient procedure to extend dynamic lot-sizing heuristics that has been overlooked by inventory management literature and practice. Its intention is to show that the extension improves the results of basic heuristics significantly. We first present a comprehensive description of the extension procedure and then test its performance in an extensive numerical study. Our analysis shows that the extension is an efficient tool to improve basic dynamic lot-sizing heuristics. The results of the paper may be used in inventory management to assist researchers in selecting dynamic lot-sizing heuristics and may be of help for practitioners as decision support.
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.
2013-11-29
... International Trade Administration Steel Threaded Rod from India: Postponement of Preliminary Determination of...'') published a notice of initiation of the antidumping duty investigation of steel threaded rod from India.\\1... later than December 20, 2013. \\1\\ See Steel Threaded Rod From India and Thailand: Initiation of...
78 FR 44532 - Steel Threaded Rod From India: Initiation of Countervailing Duty Investigation
2013-07-24
... International Trade Administration Steel Threaded Rod From India: Initiation of Countervailing Duty... (``CVD'') petition concerning imports of steel threaded rod from India, filed in proper form by All...., (collectively hereinafter ``Petitioners'').\\1\\ Petitioners are domestic producers of steel threaded rod. On July...
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.
Heuristic theory of positron-helium scattering.
Drachman, R. J.
1971-01-01
An error in a previous modified adiabatic approximation (Drachman, 1966), due to a lack of generality in the form of the short-range correlation part of the wave function for L greater than zero, is corrected heuristically by allowing the monopole suppression parameter to depend on L. An L-dependent local potential is constructed to fit the well-known positron-hydrogen s, p, and d wave phase shifts below the rearrangement threshold. The same form of potential yields a positron-helium cross-section in agreement with a recent experimental measurement near threshold.
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.
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...
How do people judge risks: availability heuristic, affect heuristic, or both?
Pachur, Thorsten; Hertwig, Ralph; Steinmann, Florian
2012-09-01
How does the public reckon which risks to be concerned about? The availability heuristic and the affect heuristic are key accounts of how laypeople judge risks. Yet, these two accounts have never been systematically tested against each other, nor have their predictive powers been examined across different measures of the public's risk perception. In two studies, we gauged risk perception in student samples by employing three measures (frequency, value of a statistical life, and perceived risk) and by using a homogeneous (cancer) and a classic set of heterogeneous causes of death. Based on these judgments of risk, we tested precise models of the availability heuristic and the affect heuristic and different definitions of availability and affect. Overall, availability-by-recall, a heuristic that exploits people's direct experience of occurrences of risks in their social network, conformed to people's responses best. We also found direct experience to carry a high degree of ecological validity (and one that clearly surpasses that of affective information). However, the relative impact of affective information (as compared to availability) proved more pronounced in value-of-a-statistical-life and perceived-risk judgments than in risk-frequency judgments. Encounters with risks in the media, in contrast, played a negligible role in people's judgments. Going beyond the assumption of exclusive reliance on either availability or affect, we also found evidence for mechanisms that combine both, either sequentially or in a composite fashion. We conclude with a discussion of policy implications of our results, including how to foster people's risk calibration and the success of education campaigns.
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.
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.
A Geographical Heuristic Routing Protocol for VANETs
Directory of Open Access Journals (Sweden)
Luis Urquiza-Aguiar
2016-09-01
Full Text Available 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.
Memorability in Context: A Heuristic Story.
Geurten, Marie; Meulemans, Thierry; Willems, Sylvie
2015-01-01
We examined children's ability to employ a metacognitive heuristic based on memorability expectations to reduce false recognitions, and explored whether these expectations depend on the context in which the items are presented. Specifically, 4-, 6-, and 9-year-old children were presented with high-, medium-, and low-memorability words, either mixed together (Experiment 1) or separated into two different lists (Experiment 2). Results revealed that only children with a higher level of executive functioning (9-year-olds) used the memorability-based heuristic when all types of items were presented within the same list. However, all children, regardless of age or executive level, implemented the metacognitive rule when high- and low-memorability words were presented in two separate lists. Moreover, the results of Experiment 2 showed that participants processed medium-memorability words more conservatively when they were presented in a low- than in a high-memorability list, suggesting that children's memorability expectations are sensitive to list-context effects.
Algorithms for Academic Search and Recommendation Systems
DEFF Research Database (Denmark)
Amolochitis, Emmanouil
2014-01-01
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...
Efficient waste reduction algorithms based on alternative ...
African Journals Online (AJOL)
This paper is concerned with wastage reduction in constrained two-dimensional guillotine- cut cutting stock problems, often called trim loss problems. A number of researchers report in the literature on algorithmic approaches to nd exact solutions for the trim loss problem. Alternative heuristic functions are investigated and ...
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.
Complexity and information flow analysis for multi-threaded programs
Ngo, Tri Minh; Huisman, Marieke
2017-07-01
This paper studies the security of multi-threaded programs. We combine two methods, i.e., qualitative and quantitative security analysis, to check whether a multi-threaded program is secure or not. In this paper, besides reviewing classical analysis models, we present a novel model of quantitative analysis where the attacker is able to select the scheduling policy. This model does not follow the traditional information-theoretic channel setting. Our analysis first studies what extra information an attacker can get if he knows the scheduler's choices, and then integrates this information into the transition system modeling the program execution. Via a case study, we compare this approach with the traditional information-theoretic models, and show that this approach gives more intuitive-matching results.
The linear and nonlinear stability of thread-annular flow.
Walton, Andrew G
2005-05-15
The surgical technique of thread injection of medical implants is modelled by the axial pressure-gradient-driven flow between concentric cylinders with a moving core. The linear stability of the flow to both axisymmetric and asymmetric perturbations is analysed asymptotically at large Reynolds number, and computationally at finite Reynolds number. The existence of multiple regions of instability is predicted and their dependence upon radius ratio and thread velocity is determined. A discrepancy in critical Reynolds numbers and cut-off velocity is found to exist between experimental results and the predictions of the linear theory. In order to account for this discrepancy, the high Reynolds number, nonlinear stability properties of the flow are analysed and a nonlinear, equilibrium critical layer structure is found, which leads to an enhanced correction to the basic flow. The predictions of the nonlinear theory are found to be in good agreement with the experimental data.
Using Tabu Search Heuristics in Solving the Vehicle Routing ...
African Journals Online (AJOL)
Nafiisah
according to Glover, is a meta-heuristic that guides a local heuristic to explore the solution space beyond local optimality. Tabu Search starts just as an ordinary local search, proceeding iteratively from one solution to the next until some stopping criteria is satisfied while making use of some strategies to avoid getting trapped ...
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
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...
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.
On the empirical performance of (T,s,S) heuristics
Babai, M. Zied; Syntetos, Aris A.; Teunter, Ruud
2010-01-01
The periodic (T,s,S) policies have received considerable attention from the academic literature. Determination of the optimal parameters is computationally prohibitive, and a number of heuristic procedures have been put forward. However, these heuristics have never been compared in an extensive
Providing Automatic Support for Heuristic Rules of Methods
Tekinerdogan, B.; Aksit, Mehmet; Demeyer, Serge; Bosch, H.G.P.; Bosch, Jan
In method-based software development, software engineers create artifacts based on the heuristic rules of the adopted method. Most CASE tools, however, do not actively assist software engineers in applying the heuristic rules. To provide an active support, the rules must be formalized, implemented
A Heuristic Hierarchical Scheme for Academic Search and Retrieval
DEFF Research Database (Denmark)
Amolochitis, Emmanouil; Christou, Ioannis T.; Tan, Zheng-Hua
2013-01-01
We present PubSearch, a hybrid heuristic scheme for re-ranking academic papers retrieved from standard digital libraries such as the ACM Portal. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score...
Comparison of greedy algorithms for α-decision tree construction
Alkhalid, Abdulaziz
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.
Formation and Evolution of a Multi-Threaded Prominence
Luna, M.; Karpen, J. T.; DeVore, C. R.
2012-01-01
We investigate the process of formation and subsequent evolution of prominence plasma in a filament channel and its overlying arcade. We construct a three-dimensional time-dependent model of a filament-channel prominence suitable to be compared with observations. We combine this magnetic field structure with one-dimensional independent simulations of many flux tubes. The magnetic structure is a three-dimensional sheared double arcade, and the thermal non-equilibrium process governs the plasma evolution. We have found that the condensations in the corona can be divided into two populations: threads and blobs. Threads are massive condensations that linger in the field line dips. Blobs are ubiquitous small condensations that are produced throughout the filament and overlying arcade magnetic structure, and rapidly fall to the chromosphere. The total prominence mass is in agreement with observations. The threads are the principal contributors to the total mass, whereas the blob contribution is small. The motion of the threads is basically horizontal, while blobs move in all directions along the field. The peak velocities for both populations are comparable, but there is a weak tendency for the velocity to increase with the inclination, and the blobs with motion near vertical have the largest values of the velocity. We have generated synthetic images of the whole structure in an H proxy and in two EUV channels of the AIA instrument aboard SDO. These images show the plasma at cool, warm and hot temperatures. The theoretical differential emission measure of our system agrees very well with observations in the temperature range log T = 4.6-5.7. We conclude that the sheared-arcade magnetic structure and plasma dynamics fit well the abundant observational evidence.
Rapid and reliable protein structure determination via chemical shift threading.
Hafsa, Noor E; Berjanskii, Mark V; Arndt, David; Wishart, David S
2017-12-01
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 structure) and to significantly outperform other shift-based or threading-based structure determination methods (in terms of top template model accuracy)-with an average TM-score performance of 0.68 (vs. 0.50-0.62 for other methods). Coupled with recent developments in 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 .
A Multi-threading Architecture for Multilevel Secure Transaction Processing
Irvine, Cynthia E.; Isa, Haruna R.; Shockley, William R.
1999-01-01
A TCB and security kernel architecture for supporting multi-threaded, queue-driven transaction processing applications in a multilevel secure environment is presented. Our design exploits hardware security features of the Intel 80x86 processor family. Intel's CPU architecture provides hardware with two distinct descriptor tables. We use one of these in the usual way for process isolation. For each process, the descriptor table holds the descriptors of "system-low" segments, such as code segme...
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.
Solving the Dial-a-Ride Problem using Genetic algorithms
DEFF Research Database (Denmark)
Bergvinsdottir, Kristin Berg; Larsen, Jesper; Jørgensen, Rene Munk
service level constraints (Quality of Service). In this paper we present a genetic algorithm for solving the DARP. The algorithm is based on the classical cluster-first route-second approach, where it alternates between assigning customers to vehicles using a genetic algorithm and solving independent...... routing problems for the vehicles using a routing heuristic. The algorithm is implemented in Java and tested on publicly available data sets....
Quantum amplitude amplification algorithm: an explanation of availability bias
Franco, Riccardo
2008-01-01
In this article, I show that a recent family of quantum algorithms, based on the quantum amplitude amplification algorithm, can be used to describe a cognitive heuristic called availability bias. The amplitude amplification algorithm is used to define quantitatively the ease of a memory task, while the quantum amplitude estimation and the quantum counting algorithms to describe cognitive tasks such as estimating probability or approximate counting.
Research on the ant colony algorithm in robot path planning
Wang, Yong; Ma, Jianming; Wang, Ying
2017-05-01
Using the A* algorithm principle proposed adaptive adjustment heuristic function, to reduce the degree of divergence algorithm; The state transition of the next ant improvement strategies, to improve the diversity of path planning solution; Control the change of the pheromone, to avoid algorithm trapped in local optimal solution; The improved ant colony algorithm makes the robot along an optimal or suboptimal path to arrive at the target.
Practical evaluation of comparative modelling and threading methods.
Schoonman, M J; Knegtel, R M; Grootenhuis, P D
1998-09-30
Six protein pairs, all with known 3D-structures, were used to evaluate different protein structure prediction tools. Firstly, alignments between a target sequence and a template sequence or structure were obtained by sequence alignment with QUANTA or by threading with THREADER, 123D and PHD Topits. Secondly, protein structure models were generated using MODELLER. The two protein structure assessment tools used were the root mean square deviation (RMSD) compared with the experimental target structure and the total 3D profile score. Also the accuracy of the active sites of models built in the absence and presence of ligands was investigated. Our study confirms that threading methods are able to yield more accurate models than comparative modelling in cases of low sequence identity (model and the models obtained by threading methods. For high sequence identities (> 30%) comparative modelling using MODELLER resulted in accurate models. Furthermore, the total 3D profile score was not always able to distinguish correct from incorrect folds when different alignment methods were used. Finally, we found it to be important to include possible ligands in the model-building process in order to prevent unrealistic filling of active site areas.
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.
A Comparative Study of Modern Heuristics on the School Timetabling Problem
Directory of Open Access Journals (Sweden)
Iosif V. Katsaragakis
2015-08-01
Full Text Available In this contribution a comparative study of modern heuristics on the school timetabling problem is presented. More precisely, we investigate the application of two population-based algorithms, namely a Particle Swarm Optimization (PSO and an Artificial Fish Swarm (AFS, on the high school timetabling problem. In order to demonstrate their efficiency and performance, experiments with real-world input data have been performed. Both algorithms proposed manage to create feasible and efficient high school timetables, thus fulfilling adequately the timetabling needs of the respective high schools. Computational results demonstrate that both algorithms manage to reach efficient solutions, most of the times better than existing approaches applied to the same school timetabling input instances using the same evaluation criteria.
Heuristics: foundations for a novel approach to medical decision making.
Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V
2015-03-01
Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.
Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence.
Naso, David; Turchiano, Biagio
2005-04-01
In many manufacturing environments, automated guided vehicles are used to move the processed materials between various pickup and delivery points. The assignment of vehicles to unit loads is a complex problem that is often solved in real-time with simple dispatching rules. This paper proposes an automated guided vehicles dispatching approach based on computational intelligence. We adopt a fuzzy multicriteria decision strategy to simultaneously take into account multiple aspects in every dispatching decision. Since the typical short-term view of dispatching rules is one of the main limitations of such real-time assignment heuristics, we also incorporate in the multicriteria algorithm a specific heuristic rule that takes into account the empty-vehicle travel on a longer time-horizon. Moreover, we also adopt a genetic algorithm to tune the weights associated to each decision criteria in the global decision algorithm. The proposed approach is validated by means of a comparison with other dispatching rules, and with other recently proposed multicriteria dispatching strategies also based on computational Intelligence. The analysis of the results obtained by the proposed dispatching approach in both nominal and perturbed operating conditions (congestions, faults) confirms its effectiveness.
Visualization for Hyper-Heuristics. Front-End Graphical User Interface
Energy Technology Data Exchange (ETDEWEB)
Kroenung, Lauren [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 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. While such automated design has great advantages, it can often be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues of usability by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics to support practitioners, as well as scientific visualization of the produced automated designs. My contributions to this project are exhibited in the user-facing portion of the developed system and the detailed scientific visualizations created from back-end data.
Lot-sizing algorithms with applications to engineering and economics
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ferreira, Jose S.
1984-01-01
The paper presents two new solution procedures for a deterministic lot size problem, a matrix algorithm and a heuristic matrix method. The algorithm is based on the dual of a linear programming model formulation of the lot size problem, and it provides optimal solutions even in the general case...
Implementation of human expert heuristics in computer supported infrared spectra interpretation
Andreev, G. N.; Argirov, O. K.
1995-03-01
A new version of the expert system EXPIRS is described that owns extended capability to mimic the human expert heuristics used for infrared spectra interpretation. The program coded in PROLOG functions on the basis of symbolic logic. It is provided with an accelerated algorithm for generation of alternative substructure sets, based on: hierarchical organization of the knowledge base, utilization of molecular formula, and a more precise subroutine for selection of the substructures. The system takes into consideration the existence of very strong absorbing characteristic groups and corrects both the current spectrum and the knowledge base in order to improve the prediction ability.
Robot path planning algorithm based on symbolic tags in dynamic environment
Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.
2017-09-01
The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.
The Statistical Mechanics of Random Set Packing and a Generalization of the Karp-Sipser Algorithm
National Research Council Canada - National Science Library
Lucibello, C; Ricci-Tersenghi, F
2014-01-01
.... We also propose a heuristic algorithm, a generalization of the celebrated Karp-Sipser one, which allows us to rigorously prove that the replica symmetric cavity method prediction is exact for certain...
Jack F. Williams
1981-01-01
Seven heuristic algorithms are discussed. Each can be used for production scheduling in an assembly network (a network where each work station has at most one immediate successor work station, but may have any number of immediate predecessor work stations), distribution scheduling in an arborescence network (a network where each warehouse or stocking point is supplied by at most one immediate predecessor stocking point, but may itself supply any number of immediate successor stocking points),...
Ranking of Storm Water Harvesting Sites Using Heuristic and Non-Heuristic Weighing Approaches
Directory of Open Access Journals (Sweden)
Shray Pathak
2017-09-01
Full Text Available Conservation of water is essential as climate change coupled with land use changes influence the distribution of water availability. Stormwater harvesting (SWH is a widely used conservation measure, which reduces pressure on fresh water resources. However, determining the availability of stormwater and identifying the suitable sites for SWH require consideration of various socio-economic and technical factors. Earlier studies use demand, ratio of runoff to demand and weighted demand distance, as the screening criteria. In this study, a Geographic Information System (GIS based screening methodology is adopted for identifying potential suitable SWH sites in urban areas as a first pass, and then a detailed study is done by applying suitability criteria. Initially, potential hotspots are identified by a concept of accumulated catchments and later the sites are screened and ranked using various screening parameters namely demand, ratio of runoff to demand and weighted demand distance. During this process, the opinion of experts for finalizing the suitable SWH sites brings subjectivity in the methodology. To obviate this, heuristic (Saaty Analytic hierarchy process (AHP and non-heuristic approaches (Entropy weight, and Principal Component Analysis (PCA weighing techniques are adapted for allotting weights to the parameters and applied in the ranking of SWH sites in Melbourne, Australia and Dehradun, India. It is observed that heuristic approach is not effective for the study area as it was affected by the subjectivity in the expert opinion. Results obtained by non-heuristic approach come out to be in a good agreement with the sites finalized for SWH by the water planners of the study area. Hence, the proposed ranking methodology has the potential for application in decision making of suitable storm water harvesting sites.
A Heuristic for Improving Transmedia Exhibition Experience
DEFF Research Database (Denmark)
Selvadurai, Vashanth; Rosenstand, Claus Andreas Foss
2017-01-01
The area of interest is transmedia experiences in exhibitions. The research question is: How to involve visitors in a transmedia experience for an existing exhibition, which bridges the pre-, during- and post-experience? Research through design, and action research are the methods used to design...... and reflect on a transmedia experience for an existing exhibition. This is framed with literature about exhibitions and transmedia, and analyzed with quantitative data from a case-study of visitors in the exhibition; this is organizationally contextualized. The contribution covers a significant gap...... 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....
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...... that seems to be well-suited for this type of system and provide some experimental results....
Combinatorial optimization theory and algorithms
Korte, Bernhard
2002-01-01
Combinatorial optimization is one of the youngest and most active areas of discrete mathematics, and is probably its driving force today. This book describes the most important ideas, theoretical results, and algorithms of this field. It is conceived as an advanced graduate text, and it can also be used as an up-to-date reference work for current research. The book includes the essential fundamentals of graph theory, linear and integer programming, and complexity theory. It covers classical topics in combinatorial optimization as well as very recent ones. The emphasis is on theoretical results and algorithms with provably good performance. Some applications and heuristics are mentioned, too.
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.
Heuristics and bias in rectal surgery.
MacDermid, Ewan; Young, Christopher J; Moug, Susan J; Anderson, Robert G; Shepherd, Heather L
2017-08-01
Deciding to defunction after anterior resection can be difficult, requiring cognitive tools or heuristics. From our previous work, increasing age and risk-taking propensity were identified as heuristic biases for surgeons in Australia and New Zealand (CSSANZ), and inversely proportional to the likelihood of creating defunctioning stomas. We aimed to assess these factors for colorectal surgeons in the British Isles, and identify other potential biases. The Association of Coloproctology of Great Britain and Ireland (ACPGBI) was invited to complete an online survey. Questions included demographics, risk-taking propensity, sensitivity to professional criticism, self-perception of anastomotic leak rate and propensity for creating defunctioning stomas. Chi-squared testing was used to assess differences between ACPGBI and CSSANZ respondents. Multiple regression analysis identified independent surgeon predictors of stoma formation. One hundred fifty (19.2%) eligible members of the ACPGBI replied. Demographics between ACPGBI and CSSANZ groups were well-matched. Significantly more ACPGBI surgeons admitted to anastomotic leak in the last year (p < 0.001). ACPGBI surgeon age over 50 (p = 0.02), higher risk-taking propensity across several domains (p = 0.044), self-belief in a lower-than-average anastomotic leak rate (p = 0.02) and belief that the average risk of leak after anterior resection is 8% or lower (p = 0.007) were all independent predictors of less frequent stoma formation. Sensitivity to criticism from colleagues was not a predictor of stoma formation. Unrecognised surgeon factors including age, everyday risk-taking, self-belief in surgical ability and lower probability bias of anastomotic leak appear to exert an effect on decision-making in rectal surgery.
Shull, Forrest; Seaman, Carolyn; Feldman, Raimund; Haingaertner, Ralf; Regardie, Myrna
2008-01-01
In 2008, we have continued analyzing the inspection data in an effort to better understand the applicability and effect of the inspection heuristics on inspection outcomes. Our research goals during this period are: 1. Investigate the effect of anomalies in the dataset (e.g. the very large meeting length values for some inspections) on our results 2. Investigate the effect of the heuristics on other inspection outcome variables (e.g. effort) 3. Investigate whether the recommended ranges can be modified to give inspection planners more flexibility without sacrificing effectiveness 4. Investigate possible refinements or modifications to the heuristics for specific subdomains (partitioned, e.g., by size, domain, or Center) This memo reports our results to date towards addressing these goals. In the next section, the first goal is addressed by describing the types of anomalies we have found in our dataset, how we have addressed them, and the effect of these changes on our previously reported results. In the following section, on "methodology", we describe the analyses we have conducted to address the other three goals and the results of these analyses are described in the "results" section. Finally, we conclude with future plans for continuing our investigation.
Cognitive Load During Route Selection Increases Reliance on Spatial Heuristics.
Brunyé, Tad T; Martis, Shaina B; Taylor, Holly A
2017-03-22
Planning routes from maps involves perceiving the symbolic environment, identifying alternate routes, and applying explicit strategies and implicit heuristics to select an option. Two implicit heuristics have received considerable attention, the southern route preference and initial segment strategy. The current study tested a prediction from decision making theory, that increasing cognitive load during route planning will increase reliance on these heuristics. In two experiments, participants planned routes while under conditions of minimal (0-back) or high (2-back) working memory load. In Experiment 1, we examined how memory load impacts the southern route heuristic. In Experiment 2, we examined how memory load impacts the initial segment heuristic. Results replicated earlier results demonstrating a southern route preference (Experiment 1) and initial segment strategy (Experiment 2), and further demonstrated that evidence for heuristic reliance is more likely under conditions of concurrent working memory load. Furthermore, the extent to which participants maintained efficient route selection latencies in the 2-back condition predicted the magnitude of this effect. Together, results demonstrate that working memory load increases the application of heuristics during spatial decision making, particularly when participants attempt to maintain quick decisions while managing concurrent task demands.
The Recognition Heuristic: A Review of Theory and Tests
Directory of Open Access Journals (Sweden)
Thorsten ePachur
2011-07-01
Full Text Available 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 that recognition supersedes further cue knowledge; (d that its use can produce the less-is-more effect—the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference.
The Recognition Heuristic: A Review of Theory and Tests
Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.
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) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266
A smart local moving algorithm for large-scale modularity-based community detection
Waltman, Ludo
2013-01-01
We introduce a new algorithm for modularity-based community detection in large networks. The algorithm, which we refer to as a smart local moving algorithm, takes advantage of a well-known local moving heuristic that is also used by other algorithms. Compared with these other algorithms, our proposed algorithm uses the local moving heuristic in a more sophisticated way. Based on an analysis of a diverse set of networks, we show that our smart local moving algorithm identifies community structures with higher modularity values than other algorithms for large-scale modularity optimization, among which the popular 'Louvain algorithm' introduced by Blondel et al. (2008). The computational efficiency of our algorithm makes it possible to perform community detection in networks with tens of millions of nodes and hundreds of millions of edges. Our smart local moving algorithm also performs well in small and medium-sized networks. In short computing times, it identifies community structures with modularity values equ...
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...
Solving Large Clustering Problems with Meta-Heuristic Search
DEFF Research Database (Denmark)
Turkensteen, Marcel; Andersen, Kim Allan; Bang-Jensen, Jørgen
In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization...... problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic...
Motor heuristics and embodied choices: how to choose and act.
Raab, Markus
2017-08-01
Human performance requires choosing what to do and how to do it. The goal of this theoretical contribution is to advance understanding of how the motor and cognitive components of choices are intertwined. From a holistic perspective I extend simple heuristics that have been tested in cognitive tasks to motor tasks, coining the term motor heuristics. Similarly I extend the concept of embodied cognition, that has been tested in simple sensorimotor processes changing decisions, to complex sport behavior coining the term embodied choices. Thus both motor heuristics and embodied choices explain complex behavior such as studied in sport and exercise psychology. Copyright © 2017 Elsevier Ltd. All rights reserved.
Heuristic Portfolio Trading Rules with Capital Gain Taxes
DEFF Research Database (Denmark)
Fischer, Marcel; Gallmeyer, Michael
2016-01-01
, 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 thus......We study the out-of-sample performance of portfolio trading strategies used when an investor faces capital gain taxation and proportional transaction costs. Overlaying simple tax trading heuristics on trading strategies improves out-of-sample performance. For medium to large transaction costs...... show that the best trading strategies balance diversification considerations and tax considerations....
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-protein complex structure predictions by multimeric threading and template recombination
Mukherjee, Srayanta; Zhang, Yang
2011-01-01
Summary The number of protein-protein complex structures is nearly 6-times smaller than that of tertiary structures in PDB which limits the power of homology-based approaches to complex structure modeling. We present a new threading-recombination approach, COTH, to boost the protein complex structure library by combining tertiary structure templates with complex alignments. The query sequences are first aligned to complex templates using a modified dynamic programming algorithm, guided by ab initio binding-site predictions. The monomer alignments are then shifted to the multimeric template framework by structural alignments. COTH was tested on 500 non-homologous dimeric proteins, which can successfully detect correct templates for half of the cases after homologous templates are excluded, which significantly outperforms conventional homology modeling algorithms. It also shows a higher accuracy in interface modeling than rigid-body docking of unbound structures from ZDOCK although with lower coverage. These data demonstrate new avenues to model complex structures from non-homologous templates. PMID:21742262
Implementation of the ATLAS trigger within the multi-threaded software framework AthenaMT
AUTHOR|(INSPIRE)INSPIRE-00225867; The ATLAS collaboration
2016-01-01
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...
Bashiri, Mahdi; Karimi, Hossein
2012-07-01
Quadratic assignment problem (QAP) is a well-known problem in the facility location and layout. It belongs to the NP-complete class. There are many heuristic and meta-heuristic methods, which are presented for QAP in the literature. In this paper, we applied 2-opt, greedy 2-opt, 3-opt, greedy 3-opt, and VNZ as heuristic methods and tabu search (TS), simulated annealing, and particle swarm optimization as meta-heuristic methods for the QAP. This research is dedicated to compare the relative percentage deviation of these solution qualities from the best known solution which is introduced in QAPLIB. Furthermore, a tuning method is applied for meta-heuristic parameters. Results indicate that TS is the best in 31%of QAPs, and the IFLS method, which is in the literature, is the best in 58 % of QAPs; these two methods are the same in 11 % of test problems. Also, TS has a better computational time among heuristic and meta-heuristic methods.
Heuristics for haplotype frequency estimation with a large number of analyzed loci
Nowotka, Michał; Nowak, Robert
Determining haplotypes with laboratory methods is an expensive and time-consuming activity therefore unsuit- able for the analysis of genetic data coming from a large number of tested individuals. Many existing algorithms for phasing genotypes operate on very impractical runtime and take into account only certain types of polymor- phisms, often without providing graphical user interface. The heuristic algorithm for estimating haplotype frequency developed in this work was examined in terms of time complexity, the speed of execution and the accuracy of results. Consequently, a Rich Internet Application that implements described algorithm has been created and its performance and accuracy to a known set of test data is analyzed. Eventually, a discussion on the architecture and the applications usability in bioinformatics applications is presented. Proposed algorithm can be used to improve the complexity of any algorithm that solves the problem of genotype phasing, which has a worse time complexity and is convergent. The algorithm is easy to scale and can achieve the desired ratio of calculations accuracy to execution time. Implemented application meets all requirements for the programs to solve problems in biology i.e. high performance, accessibility, scalability and usability.
Formal verification of a deadlock detection algorithm
Directory of Open Access Journals (Sweden)
Freek Verbeek
2011-10-01
Full Text Available Deadlock detection is a challenging issue in the analysis and design of on-chip networks. We have designed an algorithm to detect deadlocks automatically in on-chip networks with wormhole switching. The algorithm has been specified and proven correct in ACL2. To enable a top-down proof methodology, some parts of the algorithm have been left unimplemented. For these parts, the ACL2 specification contains constrained functions introduced with defun-sk. We used single-threaded objects to represent the data structures used by the algorithm. In this paper, we present details on the proof of correctness of the algorithm. The process of formal verification was crucial to get the algorithm flawless. Our ultimate objective is to have an efficient executable, and formally proven correct implementation of the algorithm running in ACL2.
Nature-Inspired Chemical Reaction Optimisation Algorithms.
Siddique, Nazmul; Adeli, Hojjat
2017-01-01
Nature-inspired meta-heuristic algorithms have dominated the scientific literature in the areas of machine learning and cognitive computing paradigm in the last three decades. Chemical reaction optimisation (CRO) is a population-based meta-heuristic algorithm based on the principles of chemical reaction. A chemical reaction is seen as a process of transforming the reactants (or molecules) through a sequence of reactions into products. This process of transformation is implemented in the CRO algorithm to solve optimisation problems. This article starts with an overview of the chemical reactions and how it is applied to the optimisation problem. A review of CRO and its variants is presented in the paper. Guidelines from the literature on the effective choice of CRO parameters for solution of optimisation problems are summarised.
Directory of Open Access Journals (Sweden)
Yun Tian
2016-01-01
Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.
Path-Wise Test Data Generation Based on Heuristic Look-Ahead Methods
Directory of Open Access Journals (Sweden)
Ying Xing
2014-01-01
Full Text Available Path-wise test data generation is generally considered an important problem in the automation of software testing. In essence, it is a constraint optimization problem, which is often solved by search methods such as backtracking algorithms. In this paper, the backtracking algorithm branch and bound and state space search in artificial intelligence are introduced to tackle the problem of path-wise test data generation. The former is utilized to explore the space of potential solutions and the latter is adopted to construct the search tree dynamically. Heuristics are employed in the look-ahead stage of the search. Dynamic variable ordering is presented with a heuristic rule to break ties, values of a variable are determined by the monotonicity analysis on branching conditions, and maintaining path consistency is achieved through analysis on the result of interval arithmetic. An optimization method is also proposed to reduce the search space. The results of empirical experiments show that the search is conducted in a basically backtrack-free manner, which ensures both test data generation with promising performance and its excellence over some currently existing static and dynamic methods in terms of coverage. The results also demonstrate that the proposed method is applicable in engineering.
Economic tour package model using heuristic
Rahman, Syariza Abdul; Benjamin, Aida Mauziah; Bakar, Engku Muhammad Nazri Engku Abu
2014-07-01
A tour-package is a prearranged tour that includes products and services such as food, activities, accommodation, and transportation, which are sold at a single price. Since the competitiveness within tourism industry is very high, many of the tour agents try to provide attractive tour-packages in order to meet tourist satisfaction as much as possible. Some of the criteria that are considered by the tourist are the number of places to be visited and the cost of the tour-packages. Previous studies indicate that tourists tend to choose economical tour-packages and aiming to visit as many places as they can cover. Thus, this study proposed tour-package model using heuristic approach. The aim is to find economical tour-packages and at the same time to propose as many places as possible to be visited by tourist in a given geographical area particularly in Langkawi Island. The proposed model considers only one starting point where the tour starts and ends at an identified hotel. This study covers 31 most attractive places in Langkawi Island from various categories of tourist attractions. Besides, the allocation of period for lunch and dinner are included in the proposed itineraries where it covers 11 popular restaurants around Langkawi Island. In developing the itinerary, the proposed heuristic approach considers time window for each site (hotel/restaurant/place) so that it represents real world implementation. We present three itineraries with different time constraints (1-day, 2-day and 3-day tour-package). The aim of economic model is to minimize the tour-package cost as much as possible by considering entrance fee of each visited place. We compare the proposed model with our uneconomic model from our previous study. The uneconomic model has no limitation to the cost with the aim to maximize the number of places to be visited. Comparison between the uneconomic and economic itinerary has shown that the proposed model have successfully achieved the objective that
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.
ThreadedComposite: A Mechanism for Building Concurrent and Parallel Ptolemy II Models
2008-12-07
exception. Be- cause the first firing produces no output, a more sensible dataflow director to use with ThreadedComposite is dynamic dataflow ( DDF ). As...iterations later than the inputs that trigger them. As of this writing, the DDF director has no period parameter, and hence will not increment time...Thus, for ThreadedComposite to work with DDF , the delay parameter ThreadedComposite Actor 14 must remain at 0.0 (or be UNDEFINED, if the nondeterminism
Adapting the Locales Framework for Heuristic Evaluation of Groupware
Directory of Open Access Journals (Sweden)
Saul Greenberg
2000-05-01
Full Text Available Heuristic evaluation is a rapid, cheap and effective way for identifying usability problems in single user systems. However, current heuristics do not provide guidance for discovering problems specific to groupware usability. In this paper, we take the Locales Framework and restate it as heuristics appropriate for evaluating groupware. These are: 1 Provide locales; 2 Provide awareness within locales; 3 Allow individual views; 4 Allow people to manage and stay aware of their evolving interactions; and 5 Provide a way to organize and relate locales to one another. To see if these new heuristics are useful in practice, we used them to inspect the interface of Teamwave Workplace, a commercial groupware product. We were successful in identifying the strengths of Teamwave as well as both major and minor interface problems.
Heuristic Method for Decision-Making in Common Scheduling Problems
National Research Council Canada - National Science Library
Edyta Kucharska
2017-01-01
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...