03929nam a22005775i 4500 978-3-031-57712-3 DE-He213 20251030112001.0 cr nn 008mamaa 240419s2024 sz | s |||| 0|eng d 9783031577123 978-3-031-57712-3 10.1007/978-3-031-57712-3 doi QA76.9.M35 UYAM bicssc COM014000 bisacsh UYAM thema Evolutionary Computation in Combinatorial Optimization [electronic resource] : 24th European Conference, EvoCOP 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings / edited by Thomas Stützle, Markus Wagner. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XI, 194 p. 41 illus. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes in Computer Science, 1611-3349 ; 14632 A Neural Network Based Guidance for a BRKGA: An Application to the Longest Common Square Subsequence Problem -- Sparse Surrogate Model for Optimization: Example of the Bus Stops Spacing Problem -- Emergence of new local search algorithms with neuro-evolution -- Q-learning Based Framework for Solving the Stochastic E-waste Collection Problem -- A memetic algorithm with adaptive operator selection for graph coloring -- Studies on Multi-objective Role Mining in ERP Systems -- Greedy heuristic guided by lexicographic excellence -- Reduction-Based MAX-3SAT with Low Nonlinearity and Lattices Under Recombination -- Where the Really Hard Quadratic Assignment Problems Are: the QAP-SAT instances -- Hardest Monotone Functions for Evolutionary Algorithms -- A Theoretical Investigation Of Termination Criteria For Evolutionary Algorithms -- Experimental and Theoretical Analysis of Local Search Optimising OBDD Variable Orderings. This book constitutes the referred proceedings of the 24th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2024, held as part of EvoStar 2024, in Aberystwyth, UK, during April 3–5, 2024. The 12 full papers presented in this book were carefully reviewed and selected from 28 submissions. They cover a variety of topics, ranging from constructive algorithms, machine learning techniques ranging from neural network based guidance to sparse surrogate models for optimization problems, the foundation of evolutionary computation algorithms and other search heuristics, to multi-objective optimization problems. . Computer science Mathematics. 64041 Computer science. 58552 Computer networks . 60157 Artificial intelligence. 58441 Mathematics of Computing. 66501 Theory of Computation. 67552 Computer Communication Networks. 65689 Artificial Intelligence. 58441 Stützle, Thomas. editor. edt http://id.loc.gov/vocabulary/relators/edt 75435 Wagner, Markus. editor. (orcid)0000-0002-3124-0061 https://orcid.org/0000-0002-3124-0061 edt http://id.loc.gov/vocabulary/relators/edt 75436 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031577116 Printed edition: 9783031577130 Lecture Notes in Computer Science, 1611-3349 ; 14632 https://doi.org/10.1007/978-3-031-57712-3 ZDB-2-SCS ZDB-2-SXCS ZDB-2-LNC 59237 59237