Academic literature on the topic 'Stochastic local search'
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Journal articles on the topic "Stochastic local search"
Mouhoub, Malek. "Stochastic local search for incremental SAT." International Journal of Knowledge-based and Intelligent Engineering Systems 9, no. 3 (September 13, 2005): 191–95. http://dx.doi.org/10.3233/kes-2005-9303.
Full textCHEN, Gong-gui. "Particle swarm optimization with stochastic local search." Journal of Computer Applications 28, no. 1 (June 30, 2008): 94–96. http://dx.doi.org/10.3724/sp.j.1087.2008.00094.
Full textKastrati, Muhamet, and Marenglen Biba. "Stochastic local search: a state-of-the-art review." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (February 1, 2021): 716. http://dx.doi.org/10.11591/ijece.v11i1.pp716-727.
Full textNekkaa, Messaouda, and Dalila Boughaci. "Hybrid Harmony Search Combined with Stochastic Local Search for Feature Selection." Neural Processing Letters 44, no. 1 (June 26, 2015): 199–220. http://dx.doi.org/10.1007/s11063-015-9450-5.
Full textHA*, Meesoon. "Stochastic Local Search in Random Constraint Satisfaction Problems." New Physics: Sae Mulli 63, no. 9 (September 30, 2013): 995–99. http://dx.doi.org/10.3938/npsm.63.995.
Full textAl-Behadili, Hayder. "Stochastic Local Search Algorithms for Feature Selection: A Review." Iraqi Journal for Electrical and Electronic Engineering 17, no. 1 (February 2, 2021): 1–10. http://dx.doi.org/10.37917/ijeee.17.1.1.
Full textPérez Cáceres, Leslie, Ignacio Araya, and Guillermo Cabrera-Guerrero. "Stochastic Local Search for the Direct Aperture Optimisation Problem." Expert Systems with Applications 182 (November 2021): 115206. http://dx.doi.org/10.1016/j.eswa.2021.115206.
Full textYu, Hang, Yu Zhang, Pengxing Cai, Junyan Yi, Sheng Li, and Shi Wang. "Stochastic Multiple Chaotic Local Search-Incorporated Gradient-Based Optimizer." Discrete Dynamics in Nature and Society 2021 (December 2, 2021): 1–16. http://dx.doi.org/10.1155/2021/3353926.
Full textKaur, Harshdeep. "LOCAL SEARCH BASED ALGORITHM FOR CVRP WITH STOCHASTIC DEMANDS." International Journal of Advanced Research in Computer Science 8, no. 7 (August 20, 2017): 1087–92. http://dx.doi.org/10.26483/ijarcs.v8i7.4468.
Full textCaramia, Massimiliano, and Paolo Dell’Olmo. "Coupling Stochastic and Deterministic Local Search in Examination Timetabling." Operations Research 55, no. 2 (April 2007): 351–66. http://dx.doi.org/10.1287/opre.1060.0354.
Full textDissertations / Theses on the topic "Stochastic local search"
Xu, Ruoxi. "Regression Model Stochastic Search via Local Orthogonalization." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1322589253.
Full textHe, Jun. "Constraints for Membership in Formal Languages under Systematic Search and Stochastic Local Search." Doctoral thesis, Uppsala universitet, Avdelningen för datalogi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-196347.
Full textBalint, Adrian [Verfasser]. "Engineering stochastic local search for the satisfiability problem / Adrian Balint." Ulm : Universität Ulm. Fakultät für Ingenieurwissenschaften und Informatik, 2014. http://d-nb.info/1046623567/34.
Full textChiarandini, Marco. "Stochastic Local Search Methods for Highly Constrained Combinatorial Optimisation Problems." Phd thesis, [S.l. : s.n.], 2005. https://tuprints.ulb.tu-darmstadt.de/595/1/ChiarandiniPhD.pdf.
Full textCai, Shaowei. "Novel Local Search Methods for Satisfiability." Thesis, Griffith University, 2015. http://hdl.handle.net/10072/366424.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Integrated and Intelligent Systems
Science, Environment, Engineering and Technology
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Paquete, Luís F. "Stochastic local search algorithms for multiobjective combinatorial optimization methods and analysis." Berlin Aka, 2005. http://deposit.ddb.de/cgi-bin/dokserv?id=2770886&prov=M&dok_var=1&dok_ext=htm.
Full textBin, Hussin Mohamed Saifullah. "Stochastic local search algorithms for single and bi-objective quadratic assignment problems." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/222286.
Full textDoctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
Garattoni, Lorenzo. "Advanced stochastic local search methods for automatic design of Boolean network robots." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3443/.
Full textBianchi, Leonora. "Ant colony optimization and local search for the probabilistic traveling salesman problem: a case study in stochastic combinatorial optimization." Doctoral thesis, Universite Libre de Bruxelles, 2006. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210877.
Full textOptimization problems under uncertainty are complex and difficult, and often classical algorithmic approaches based on mathematical and dynamic programming are able to solve only very small problem instances. For this reason, in recent years metaheuristic algorithms such as Ant Colony Optimization, Evolutionary Computation, Simulated Annealing, Tabu Search and others, are emerging as successful alternatives to classical approaches.
In this thesis, metaheuristics that have been applied so far to SCOPs are introduced and the related literature is thoroughly reviewed. In particular, two properties of metaheuristics emerge from the survey: they are a valid alternative to exact classical methods for addressing real-sized SCOPs, and they are flexible, since they can be quite easily adapted to solve different SCOPs formulations, both static and dynamic. On the base of the current literature, we identify the following as the key open issues in solving SCOPs via metaheuristics:
(1) the design and integration of ad hoc, fast and effective objective function approximations inside the optimization algorithm;
(2) the estimation of the objective function by sampling when no closed-form expression for the objective function is available, and the study of methods to reduce the time complexity and noise inherent to this type of estimation;
(3) the characterization of the efficiency of metaheuristic variants with respect to different levels of stochasticity in the problem instances.
We investigate the above issues by focusing in particular on a SCOP belonging to the class of vehicle routing problems: the Probabilistic Traveling Salesman Problem (PTSP). For the PTSP, we consider the Ant Colony Optimization metaheuristic and we design efficient local search algorithms that can enhance its performance. We obtain state-of-the-art algorithms, but we show that they are effective only for instances above a certain level of stochasticity, otherwise it is more convenient to solve the problem as if it were deterministic.
The algorithmic variants based on an estimation of the objective function by sampling obtain worse results, but qualitatively have the same behavior of the algorithms based on the exact objective function, with respect to the level of stochasticity. Moreover, we show that the performance of algorithmic variants based on ad hoc approximations is strongly correlated with the absolute error of the approximation, and that the effect on local search of ad hoc approximations can be very degrading.
Finally, we briefly address another SCOP belonging to the class of vehicle routing problems: the Vehicle Routing Problem with Stochastic Demands (VRPSD). For this problem, we have implemented and tested several metaheuristics, and we have studied the impact of integrating in them different ad hoc approximations.
Doctorat en sciences appliquées
info:eu-repo/semantics/nonPublished
Goodson, Justin Christopher. "Solution methodologies for vehicle routing problems with stochastic demand." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/675.
Full textBooks on the topic "Stochastic local search"
Braziunas, Darius. Stochastic local search for POMDP controllers. Ottawa: National Library of Canada, 2003.
Find full textThomas, Stützle, ed. Stochastic local search: Foundations and applications. San Francisco, CA: Morgan Kaufmann Publishers, 2005.
Find full textStützle, Thomas, Mauro Birattari, and Holger H. Hoos, eds. Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74446-7.
Full textStützle, Thomas, Mauro Birattari, and Holger H. Hoos, eds. Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03751-1.
Full textThomas, Stützle, Birattari Mauro, and Hoos Holger H, eds. Engineering stochastic local search algorithms: Designing, implementing and analyzing effective heuristics : international workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007 : proceedings. Berlin: Springer, 2007.
Find full textH, Hoos Holger, Birattari Mauro, and SpringerLink (Online service), eds. Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: Second International Workshop, SLS 2009, Brussels, Belgium, September 3-4, 2009. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.
Find full textStochastic Local Search. Elsevier, 2005. http://dx.doi.org/10.1016/b978-1-55860-872-6.x5016-1.
Full textHoos, Holger H. Stochastic Local Search - Methods, Models, Applications. Ios Pr Inc, 1999.
Find full textHoos, Holger H., and Thomas Stützle. Stochastic Local Search: Foundations and Applications. Elsevier Science & Technology Books, 2004.
Find full textAbed, Sa'Ed. Efficient Implementation of Parallel SAT Solver Based Stochastic Local Search. Nova Science Publishers, Incorporated, 2020.
Find full textBook chapters on the topic "Stochastic local search"
Bhatnagar, S., H. Prasad, and L. Prashanth. "Deterministic Algorithms for Local Search." In Stochastic Recursive Algorithms for Optimization, 13–15. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4285-0_2.
Full textHoos, Holger H., and Thomas Stützle. "Stochastic Local Search Algorithms: An Overview." In Springer Handbook of Computational Intelligence, 1085–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-43505-2_54.
Full textde Lima Martins, Simone, Isabel Rosseti, and Alexandre Plastino. "Data Mining in Stochastic Local Search." In Handbook of Heuristics, 39–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-07124-4_11.
Full textMartins, Simone de Lima, Isabel Rosseti, and Alexandre Plastino. "Data Mining in Stochastic Local Search." In Handbook of Heuristics, 1–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-07153-4_11-1.
Full textDi Gaspero, Luca, and Andrea Roli. "Flexible Stochastic Local Search for Haplotype Inference." In Lecture Notes in Computer Science, 74–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-11169-3_6.
Full textYu, Tong, Branislav Kveton, and Ole J. Mengshoel. "Thompson Sampling for Optimizing Stochastic Local Search." In Machine Learning and Knowledge Discovery in Databases, 493–510. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71249-9_30.
Full textWinfree, Erik. "Chemical Reaction Networks and Stochastic Local Search." In Lecture Notes in Computer Science, 1–20. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26807-7_1.
Full textAraujo, Janniele A. S., Haroldo G. Santos, Davi D. Baltar, Túlio A. M. Toffolo, and Tony Wauters. "Neighborhood Composition Strategies in Stochastic Local Search." In Hybrid Metaheuristics, 118–30. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39636-1_9.
Full textCodognet, Philippe, and Daniel Diaz. "Yet Another Local Search Method for Constraint Solving." In Stochastic Algorithms: Foundations and Applications, 73–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45322-9_5.
Full textArcuri, Andrea. "Theoretical Analysis of Local Search in Software Testing." In Stochastic Algorithms: Foundations and Applications, 156–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04944-6_13.
Full textConference papers on the topic "Stochastic local search"
Lasisi, Ramoni O., and Robert DuPont. "Augmenting Stochastic Local Search with Heuristics." In 2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2018. http://dx.doi.org/10.1109/uemcon.2018.8796721.
Full textPošik, Petr. "Stochastic local search in continuous domains." In the 12th annual conference comp. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1830761.1830830.
Full textAchlioptas, Dimitris, and Fotis Iliopoulos. "Focused Stochastic Local Search and the Lovász Local Lemma." In Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2015. http://dx.doi.org/10.1137/1.9781611974331.ch141.
Full textSantiago, Rafael, and Luís C. Lamb. "Efficient Stochastic Local Search for Modularity Maximization." In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908961.2909003.
Full textHossain, Muktadir, Tajkia Tasnim, Swakkhar Shatabda, and Dewan M. Farid. "Stochastic local search for pattern set mining." In 2014 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE, 2014. http://dx.doi.org/10.1109/skima.2014.7083547.
Full textMengshoel, Ole Jakob, Tong Yu, Jon Riege, and Eirik Flogard. "Stochastic local search for efficient hybrid feature selection." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459438.
Full textBahamida, Bachir, and Dalila Boughaci. "Intrusion Detection Using Fuzzy Stochastic Local Search Classifier." In 2012 11th Mexican International Conference on Artificial Intelligence (MICAI). IEEE, 2012. http://dx.doi.org/10.1109/micai.2012.17.
Full textvan der Lee, Tim, Georgios Exarchakos, and Sonia Heemstra de Groot. "Distributed Wireless Network Optimization With Stochastic Local Search." In 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2020. http://dx.doi.org/10.1109/ccnc46108.2020.9045189.
Full textDong, Sheqin, Fan Guo, Jun Yuan, Rensheng Wang, and Xianlong Hong. "Stochastic Local Search Using the Search Space Smoothing Meta-Heuristic:A Case Study." In 9th Joint Conference on Information Sciences. Paris, France: Atlantis Press, 2006. http://dx.doi.org/10.2991/jcis.2006.213.
Full textBrunato, Mauro, and Roberto Battiti. "Stochastic Local Search for direct training of threshold networks." In 2015 International Joint Conference on Neural Networks (IJCNN). IEEE, 2015. http://dx.doi.org/10.1109/ijcnn.2015.7280770.
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