Letteratura scientifica selezionata sul tema "Encodings and local search operators"
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Articoli di riviste sul tema "Encodings and local search operators":
Raidl, Günther R., e Jens Gottlieb. "Empirical Analysis of Locality, Heritability and Heuristic Bias in Evolutionary Algorithms: A Case Study for the Multidimensional Knapsack Problem". Evolutionary Computation 13, n. 4 (dicembre 2005): 441–75. http://dx.doi.org/10.1162/106365605774666886.
Varnamkhasti, M. Jalali. "A genetic algorithm rooted in integer encoding and fuzzy controller". IAES International Journal of Robotics and Automation (IJRA) 8, n. 2 (1 giugno 2019): 113. http://dx.doi.org/10.11591/ijra.v8i2.pp113-124.
Gao, Yilong, Zhiqiang Xie, Xinyang Liu, Wei Zhou e Xu Yu. "Integrated scheduling algorithm based on the priority constraint table for complex products with tree structure". Advances in Mechanical Engineering 12, n. 12 (dicembre 2020): 168781402098520. http://dx.doi.org/10.1177/1687814020985206.
Jalali Varnamkhasti, M., e L. S. Lee. "A Fuzzy Genetic Algorithm Based on Binary Encoding for Solving Multidimensional Knapsack Problems". Journal of Applied Mathematics 2012 (2012): 1–23. http://dx.doi.org/10.1155/2012/703601.
Jiang, Tianhua. "A Hybrid Grey Wolf Optimization for Job Shop Scheduling Problem". International Journal of Computational Intelligence and Applications 17, n. 03 (settembre 2018): 1850016. http://dx.doi.org/10.1142/s1469026818500165.
Yang, Jinfeng, e Hua Xu. "Hybrid Memetic Algorithm to Solve Multiobjective Distributed Fuzzy Flexible Job Shop Scheduling Problem with Transfer". Processes 10, n. 8 (1 agosto 2022): 1517. http://dx.doi.org/10.3390/pr10081517.
Weise, Thomas. "Software - motipy: the Metaheuristic Optimization in Python Library". ACM SIGEVOlution 16, n. 4 (dicembre 2023): 1–2. http://dx.doi.org/10.1145/3638461.3638464.
Zhang, L., e U. Kleine. "A novel bottom-left packing genetic algorithm for analog module placement". Advances in Radio Science 1 (5 maggio 2003): 191–96. http://dx.doi.org/10.5194/ars-1-191-2003.
Salcedo-Sanz, S., J. Del Ser e Z. W. Geem. "An Island Grouping Genetic Algorithm for Fuzzy Partitioning Problems". Scientific World Journal 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/916371.
Yu, Zhenao, Peng Duan, Leilei Meng, Yuyan Han e Fan Ye. "Multi-objective path planning for mobile robot with an improved artificial bee colony algorithm". Mathematical Biosciences and Engineering 20, n. 2 (2022): 2501–29. http://dx.doi.org/10.3934/mbe.2023117.
Tesi sul tema "Encodings and local search operators":
Tsogbetse, Israël. "Etude de codages et voisinages d'un espace de recherche. Application à l'ordonnancement de tâches dans des cas contraints". Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCA001.
Metaheuristics are optimization problem-solving methods that primarily rely on an abstract representation of solutions in the form of direct or indirect encoding. Improving a solution or a set of solutions in parallel is achieved through manipulations of these encodings and algorithms evaluating the quality of associated solutions. The transition from one solution to another involves the use of one or more operators to explore the search space. Generally, metaheuristics utilize these operators to iteratively enhance solutions until reaching a local (or global) optimum. A plethora of metaheuristics has been proposed to address combinatorial optimization problems, including task scheduling problems. These ones are often dedicated to specific classes of instances. In this context, researchers frequently propose algorithms that combine various methods, striving to optimize parameters across different parts of their algorithms. However, the achieved performance is often comparable, and efficiency depends on the class of instances addressed. While solution encodings and neighborhood operators are recognized as essential components within metaheuristics, they are rarely jointly examined in an analytical and scientific manner.This thesis aims to characterize solution encodings and neighborhood operators commonly used in scheduling, particularly for the job shop problem and for one of its variants, in which the objective is to minimize the makespan. The ambition is to exploit the properties of the search spaces induced by these encodings and operators to enhance the design of metaheuristics. The approach applied in our study is structured into two main parts, with a gradation in the complexity of the job shop problem. The first part focuses on characterizing search spaces through a fitness landscape analysis, using metrics from the literature. The second part involves evaluating the performance of various combinations of encodings and neighborhood operators with the aim of identifying potential correlations with landscape properties. This is done to provide recommendations for the design of metaheuristics. This approach is initially applied to a basic job shop and then to a more constrained variant: the flexible job shop with transportation constraints. Our work highlights the challenge of linking the performance of tested combinations with standard metrics. The comparison of results obtained for the basic problem and its more constrained variant leads us to express reservations about a systematic generalization of encoding and operator characteristics for this category of optimization problems
Capitoli di libri sul tema "Encodings and local search operators":
Kordos, Mirosław, Rafał Kulka, Tomasz Steblik e Rafał Scherer. "Local Search in Selected Crossover Operators". In Computational Science – ICCS 2022, 369–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08757-8_31.
Chen, Yujie, Philip Mourdjis, Fiona Polack, Peter Cowling e Stephen Remde. "Evaluating Hyperheuristics and Local Search Operators for Periodic Routing Problems". In Evolutionary Computation in Combinatorial Optimization, 104–20. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30698-8_8.
Freisleben, Bernd, e Peter Merz. "New genetic local search operators for the traveling salesman problem". In Parallel Problem Solving from Nature — PPSN IV, 890–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61723-x_1052.
Aboutaib, Brahim, Sébastien Verel, Cyril Fonlupt, Bilel Derbel, Arnaud Liefooghe e Belaïd Ahiod. "On Stochastic Fitness Landscapes: Local Optimality and Fitness Landscape Analysis for Stochastic Search Operators". In Parallel Problem Solving from Nature – PPSN XVI, 97–110. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58115-2_7.
Nigam, Vivek, Giselle Reis, Samar Rahmouni e Harald Ruess. "Proof Search and Certificates for Evidential Transactions". In Automated Deduction – CADE 28, 234–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79876-5_14.
Bansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat e Atulya K. Nagar. "Advancements in the Sine Cosine Algorithm". In Sine Cosine Algorithm for Optimization, 87–103. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_5.
Durgut, Rafet, e Mehmet Emin Aydin. "Multi Strategy Search with Crow Search Algorithm". In Optimization Algorithms [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.102862.
Ould Sidi, Hamed, Rachid Ellaia, Emmanuel Pagnacco e Ahmed Tchvagha Zeine. "An Immune Multiobjective Optimization with Backtracking Search Algorithm Inspired Recombination". In Search Algorithm - Essence of Optimization. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.100306.
Atti di convegni sul tema "Encodings and local search operators":
Yin, Shuo, e Guoqiang Zhong. "LGI-GT: Graph Transformers with Local and Global Operators Interleaving". In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/501.
Tanigaki, Yuki, Hiroyuki Masuda, Yu Setoguchi, Yusuke Nojima e Hisao Ishibuchi. "Algorithm structure optimization by choosing operators in multiobjective genetic local search". In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7256980.
Green, Jeremy R., Anthony Francis, Parikshit Junnarkar, Miao Chuan, Thomas Rae e Hartmut Wittig. "Search for a bound H-dibaryon using local six-quark interpolating operators". In The 32nd International Symposium on Lattice Field Theory. Trieste, Italy: Sissa Medialab, 2015. http://dx.doi.org/10.22323/1.214.0107.
Pourhassan, Mojgan, e Frank Neumann. "On the Impact of Local Search Operators and Variable Neighbourhood Search for the Generalized Travelling Salesperson Problem". In GECCO '15: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2739480.2754656.
Domınguez-Isidro, Saul, Efren Mezura-Montes e Guillermo Leguizamon. "Performance comparison of local search operators in differential evolution for constrained numerical optimization problems". In 2014 IEEE Symposium on Differential Evolution (SDE). IEEE, 2014. http://dx.doi.org/10.1109/sde.2014.7031530.
Gao, Kaizhou, Yicheng Zhang, Yi Zhang e Rong Su. "A meta-heuristic with ensemble of local search operators for urban traffic light optimization". In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. http://dx.doi.org/10.1109/ssci.2017.8285317.
Liu, Xin-Xin, Dong Liu, Qiang Yang, Xiao-Fang Liu, Wei-Jie Yu e Jun Zhang. "Comparative Analysis of Five Local Search Operators on Visiting Constrained Multiple Traveling Salesmen Problem". In 2021 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2021. http://dx.doi.org/10.1109/ssci50451.2021.9659963.
Rodrigues da Cruz, André, Rodrigo Tomás Nogueira Cardoso, Elizabeth Fialho Wanner e Ricardo Takahashi. "Local Search Operators Based on Linear-Quadratic Approximations for Multiobjective Problems on a Budget Scenario". In ANAIS DO SIMPóSIO BRASILEIRO DE PESQUISA OPERACIONAL. Rio de Janeiro - Rio de Janeiro, Brasil: Galoa, 2018. http://dx.doi.org/10.59254/sbpo-2018-85409.
Dominguez-Isidro, Saul, e Efren Mezura-Montes. "Study of direct local search operators influence in memetic differential evolution for constrained numerical optimization problems". In 2017 International Conference on Electronics, Communications and Computers (CONIELECOMP). IEEE, 2017. http://dx.doi.org/10.1109/conielecomp.2017.7891831.
Katayama, Kengo, Yuto Akagi, Elis Kulla, Hideo Minamihara e Noritaka Nishihara. "New Kick Operators in Iterated Local Search Based Metaheuristic for Solving the Node Placement Problem in Multihop Networks". In 2014 17th International Conference on Network-Based Information Systems (NBiS). IEEE, 2014. http://dx.doi.org/10.1109/nbis.2014.35.