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Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 21st European Conference, EvoCOP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Christine Zarges, Sébastien Verel



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Titolo: Evolutionary Computation in Combinatorial Optimization [[electronic resource] ] : 21st European Conference, EvoCOP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / / edited by Christine Zarges, Sébastien Verel Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (xiv, 237 pages) : illustrations
Disciplina: 005.432
Soggetto topico: Computer science—Mathematics
Computer systems
Computer science
Artificial intelligence
Computer programming
Software engineering
Mathematics of Computing
Computer System Implementation
Theory of Computation
Artificial Intelligence
Programming Techniques
Software Engineering
Persona (resp. second.): VerelSébastien
ZargesChristine
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: A Novel Ant Colony Optimization Strategy for the Quantum Circuit Compilation Problem -- Hybridization of Racing Methods with Evolutionary Operators for Simulation Optimization of Traffic Lights Programs -- Decomposition-based Multi-objective Landscape Features and Automated Algorithm Selection -- MATE: A Model-Based Algorithm Tuning Engine -- An Improvement Heuristic Based on Variable Neighborhood Search for a Dynamic Orienteering Problem -- Runtime Analysis of the (mu+1)-EA on the Dynamic BinVal Function -- Tabu-Driven Quantum Neighborhood Samplers -- On Hybrid Heuristics for Steiner Trees on the Plane with Obstacles -- Flowshop NEH-Based Heuristic Recommendation -- Stagnation Detection with Randomized Local Search -- An Artificial Immune System for Black Box Test Case Selection -- Symmetry Breaking for Voting Mechanisms -- A Heuristic Algorithm for School Bus Routing with Bus Stop Selection -- Hybrid Heuristic and Metaheuristic for Solving Electric Vehicle Charging Scheduling Problem.
Sommario/riassunto: This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP. The 14 revised full papers presented in this book were carefully reviewed and selected from 42 submissions. They cover a wide spectrum of topics, ranging from the foundations of evolutionary algorithms and other search heuristics to their accurate design and application to combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of core components of metaheuristics, the clever design of their search principles, and their careful selection and configuration. Applications cover problem domains such as scheduling, routing, search-based software engineering and general graph problems. The range of topics covered in this volume reflects the current state of research in the fields of evolutionary computation and combinatorial optimization.
Titolo autorizzato: Evolutionary Computation in Combinatorial Optimization  Visualizza cluster
ISBN: 3-030-72904-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996464384803316
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Serie: Theoretical Computer Science and General Issues, . 2512-2029 ; ; 12692