Evolutionary Computation in Combinatorial Optimization

20th European Conference, EvoCOP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings

AvLuís Paquete,Christine Zarges

Häftad, Engelska, 2020

Del 12102 i serien Lecture Notes in Computer Science

565 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

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.

Produktinformation

Utgivningsdatum:2020-03-10
Mått:155 x 235 x 14 mm
Vikt:382 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:231
Förlag:Springer Nature Switzerland AG
ISBN:9783030436797

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Nätverk och kommunikation inom Data och IT
Databaser inom Data och IT

Innehållsförteckning

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.