Meta-Heuristics

Advances and Trends in Local Search Paradigms for Optimization

  • Stefan Voß
  • Silvano Martello
  • Ibrahim H. Osman
  • Catherine Roucairol

Table of contents

  1. Front Matter
    Pages i-xii
  2. Tabu Search

    1. Front Matter
      Pages 1-1
    2. Luis Cavique, César Rego, Isabel Themido
      Pages 37-47
    3. Raphaël Dorne, Jin-Kao Hao
      Pages 77-92
    4. Fred Glover, Gary Kochenberger, Bahram Alidaee, Mohammed Amini
      Pages 93-109
    5. Redouane Mechti, Stephane Poujade, Catherine Roucairol, Bernard Lemarié
      Pages 155-174
    6. Eugeniusz Nowicki, Czesław Smutnicki
      Pages 175-189
  3. Combined and Hybrid Approaches

    1. Front Matter
      Pages 191-191
    2. Stuart M. Allen, Steve Hurley, Derek H. Smith, Stefan U. Thiel
      Pages 191-204
    3. Foued Ben Abdelaziz, Saoussen Krichen, Jouhaina Chaouachi
      Pages 205-212
  4. Genetic and Evolutionary Algorithms

    1. Front Matter
      Pages 231-231

About this book

Introduction

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.

Keywords

Constraint satisfaction actuator algorithm algorithms combinatorial optimization evolutionary algorithm genetic algorithms global optimization heuristics metaheuristic model optimization programming scheduling

Editors and affiliations

  • Stefan Voß
    • 1
  • Silvano Martello
    • 2
  • Ibrahim H. Osman
    • 3
  • Catherine Roucairol
    • 4
  1. 1.Technical University of BraunschweigGermany
  2. 2.University of BolognaItaly
  3. 3.University of KentUK
  4. 4.University of VersaillesFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-5775-3
  • Copyright Information Kluwer Academic Publishers 1999
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7646-0
  • Online ISBN 978-1-4615-5775-3
  • About this book