03733nam a22005295i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001500172072001700187072002300204072001600227245024800243250001800491264006900509300004300578336002600621337002600647338003600673347002400709490005900733505093300792520065301725650004202378650002902420650003202449650003602481650003702517650003402554650004402588650003602632700008702668700015102755710003402906773002602940776003602966776003603002830005903038856004603097912001403143912001503157912001403172999001703186978-3-031-57712-3DE-He21320251030112001.0cr nn 008mamaa240419s2024    sz |    s    |||| 0|eng d  a97830315771239978-3-031-57712-37 a10.1007/978-3-031-57712-32doi 4aQA76.9.M35 7aUYAM2bicssc 7aCOM0140002bisacsh 7aUYAM2thema10aEvolutionary Computation in Combinatorial Optimizationh[electronic resource] :b24th European Conference, EvoCOP 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings /cedited by Thomas Stützle, Markus Wagner.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXI, 194 p. 41 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aLecture Notes in Computer Science,x1611-3349 ;v146320 aA 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.  aThis 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. . 0aComputer sciencexMathematics.964041 0aComputer science.958552 0aComputer networks .960157 0aArtificial intelligence.95844114aMathematics of Computing.96650124aTheory of Computation.96755224aComputer Communication Networks.96568924aArtificial Intelligence.9584411 aStützle, Thomas.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9754351 aWagner, Markus.eeditor.0(orcid)0000-0002-3124-00611https://orcid.org/0000-0002-3124-00614edt4http://id.loc.gov/vocabulary/relators/edt9754362 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303157711608iPrinted edition:z9783031577130 0aLecture Notes in Computer Science,x1611-3349 ;v1463240uhttps://doi.org/10.1007/978-3-031-57712-3  aZDB-2-SCS  aZDB-2-SXCS  aZDB-2-LNC  c59237d59237