UID:
almahu_9948435923202882
Umfang:
XIV, 231 p. 82 illus., 46 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2020.
ISBN:
9783030436803
Serie:
Theoretical Computer Science and General Issues ; 12102
Inhalt:
This book constitutes the refereed proceedings of the 20th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoMUSART and EvoApplications. The 14 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers cover a wide spectrum of topics, ranging from the foundations of evolutionary computation algorithms and other search heuristics, to their accurate design and application to combinatorial optimization problems.
Anmerkung:
Optimizing Prices and Periods in Time-of-use Electricity Tariff Design Using Bilevel Programming -- An Algebraic Approach for the Search Space of Permutations with Repetition -- A Comparison of Genetic Representations for Multi-Objective Shortest Path Problems on Multigraphs -- The Univariate Marginal Distribution Algorithm Copes well with Deception and Epistasis -- A Beam Search Approach to the Traveling Tournament Problem -- Cooperative Parallel SAT Local Search with Path Relinking -- Dynamic Compartmental Models for Large Multi-Objective Landscapes and Performance Estimation -- Fitness Landscape Analysis of Automated Machine Learning Search Spaces -- On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D -- A Grouping Genetic Algorithm for Multi Depot Pickup and Delivery Problems with Time Windows and Heterogeneous Vehicle Fleets -- MILPIBEA: Algorithm for Multi-Objective Features Selection in (Evolving) Software Product Lines -- A Group Genetic Algorithm for Resource Allocation in Container-Based Clouds -- The Local Optima Level in Chemotherapy Schedule Optimisation -- Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783030436797
Weitere Ausg.:
Printed edition: ISBN 9783030436810
Sprache:
Englisch
DOI:
10.1007/978-3-030-43680-3
URL:
https://doi.org/10.1007/978-3-030-43680-3
