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Evolutionary Computation in Combinatorial Optimization

19th European Conference, EvoCOP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings

  • Arnaud Liefooghe
  • Luís Paquete
Conference proceedings EvoCOP 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11452)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 11452)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Thomas Jatschka, Tobias Rodemann, Günther R. Raidl
    Pages 1-16
  3. Valentino Santucci, Marco Baioletti, Gabriele Di Bari, Alfredo Milani
    Pages 17-32
  4. Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
    Pages 66-82
  5. Bilal Messaoudi, Ammar Oulamara, Nastaran Rahmani
    Pages 83-98
  6. Paul McMenemy, Nadarajen Veerapen, Jason Adair, Gabriela Ochoa
    Pages 99-114
  7. Francisco Chicano, Gabriela Ochoa, Darrell Whitley, Renato Tinós
    Pages 131-146
  8. Werner Mostert, Katherine M. Malan, Gabriela Ochoa, Andries P. Engelbrecht
    Pages 147-162
  9. Sarah L. Thomson, Gabriela Ochoa, Sébastien Verel
    Pages 163-178
  10. Marcos Diez García, Alberto Moraglio
    Pages 179-195
  11. Bilal Messaoudi, Ammar Oulamara, Nastaran Rahmani
    Pages C1-C1
  12. Back Matter
    Pages 213-213

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 19th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* 2019 events EuroGP, EvoMUSART and EvoApplications.

The 14 revised full papers presented 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 both single- and multi-objective combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of metaheuristics core components, the clever design of their search principles, and their careful selection and configuration. Applications cover domains such as scheduling, routing, partitioning and general graph problems.

Keywords

artificial intelligence automatic algorithm configuration combinatorial mathematics combinatorial optimization combinatorial problems evolutionary algorithms genetic algorithms graph theory heuristic methods local optima metaheuristics particle swarm optimization (pso) problem solving routing protocols runtime analysis search spaces simulated annealing stochastic local search traveling salesman problem

Editors and affiliations

  1. 1.University of LilleLilleFrance
  2. 2.University of CoimbraCoimbraPortugal

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-16711-0
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-16710-3
  • Online ISBN 978-3-030-16711-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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