Hybrid Metaheuristics

Powerful Tools for Optimization

  • Christian Blum
  • Günther R. Raidl
Part of the Artificial Intelligence: Foundations, Theory, and Algorithms book series (AIFTA)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Christian Blum, Günther R. Raidl
    Pages 1-26
  3. Christian Blum, Günther R. Raidl
    Pages 27-44
  4. Christian Blum, Günther R. Raidl
    Pages 45-62
  5. Christian Blum, Günther R. Raidl
    Pages 63-82
  6. Christian Blum, Günther R. Raidl
    Pages 101-125
  7. Christian Blum, Günther R. Raidl
    Pages 127-136
  8. Back Matter
    Pages 137-157

About this book

Introduction

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives.

The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

Keywords

Heuristics Metaheuristics Hybrid Metaheuristics Dynamic Programming CPLEX Constraint Programming Optimization Cominatorial Optimization Neighborhood Search Integer Linear Programming (ILP)

Authors and affiliations

  • Christian Blum
    • 1
  • Günther R. Raidl
    • 2
  1. 1.Dept Comp Sci & Artificial IntelligenceUniversity of the Basque CountrySan SebastianSpain
  2. 2.Algorithms and Data Structures GroupVienna University of TechnologyWienAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-30883-8
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-30882-1
  • Online ISBN 978-3-319-30883-8
  • Series Print ISSN 2365-3051
  • Series Online ISSN 2365-306X
  • About this book