Evolutionary Computation in Combinatorial Optimization

18th European Conference, EvoCOP 2018, Parma, Italy, April 4–6, 2018, Proceedings

  • Arnaud Liefooghe
  • Manuel López-Ibáñez
Conference proceedings EvoCOP 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10782)

Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 10782)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Sarah L. Thomson, Sébastien Verel, Gabriela Ochoa, Nadarajen Veerapen, Paul McMenemy
    Pages 18-33
  3. Paul McMenemy, Nadarajen Veerapen, Gabriela Ochoa
    Pages 34-49
  4. Sara Tari, Matthieu Basseur, Adrien Goëffon
    Pages 50-66
  5. Anas Elhag, Ender Özcan
    Pages 101-115
  6. Alex Gliesch, Marcus Ritt, Mayron C. O. Moreira
    Pages 158-173
  7. Abhishek Ray, Mario Ventresca
    Pages 174-188
  8. Sarah L. Thomson, Sébastien Verel, Gabriela Ochoa, Nadarajen Veerapen, Paul McMenemy
    Pages E1-E1
  9. Back Matter
    Pages 189-189

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 18th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events EuroGP, EvoMUSART and EvoApplications.

 The 12 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 by means of automatic algorithm configuration and hyper-heuristics. Applications cover conventional academic domains such as NK landscapes, binary quadratic programming, traveling salesman, vehicle routing, or scheduling problems, and also include real-world domains in clustering, commercial districting and winner determination.

Keywords

artificial intelligence automatic algorithm configuration combinatorial optimization evolutionary algorithms genetic algorithms graph theory heuristic algorithms heuristic methods local optima multiobjective optimization runtime analysis problem solving scheduling algorithms scheduling problem search methodologies simulated annealing tabu search

Editors and affiliations

  1. 1.University of LilleLilleFrance
  2. 2.University of ManchesterManchesterUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-77449-7
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-77448-0
  • Online ISBN 978-3-319-77449-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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