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Advances in Multi-Objective Nature Inspired Computing

  • Book
  • © 2010

Overview

Editors:
  1. Carlos A. Coello Coello

    1. Depto. de Computación, CINVESTAV-IPN, México, Mexico

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  2. Clarisse Dhaenens

    1. Parc scientifique de la Haute-Borne, LIFL/CNRS/Polytech’Lille/INRIA, Villeneuve d’Ascq, France

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  3. Laetitia Jourdan

    1. Parc scientifique de la Haute-Borne, INRIA/LIFL/CNRS, Villeneuve d’Ascq, France

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  • Recent research in multi-objective nature inspired computing

Part of the book series: Studies in Computational Intelligence (SCI, volume 272)

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Table of contents (8 chapters)

  1. Front Matter

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  2. Multi-Objective Combinatorial Optimization: Problematic and Context

    • Carlos A. Coello Coello, Clarisse Dhaenens, Laetitia Jourdan
    Pages 1-21

  3. Approximating Pareto-Optimal Sets Using Diversity Strategies in Evolutionary Multi-Objective Optimization

    • Christian Horoba, Frank Neumann
    Pages 23-44

  4. On the Velocity Update in Multi-Objective Particle Swarm Optimizers

    • Juan J. Durillo, Antonio J. Nebro, José García-Nieto, Enrique Alba
    Pages 45-62

  5. Approaching Dynamic Multi-Objective Optimization Problems by Using Parallel Evolutionary Algorithms

    • Mario Cámara, Julio Ortega, Francisco de Toro
    Pages 63-86

  6. ParadisEO-MOEO: A Software Framework for Evolutionary Multi-Objective Optimization

    • Arnaud Liefooghe, Laetitia Jourdan, Thomas Legrand, Jérémie Humeau, El-Ghazali Talbi
    Pages 87-117

  7. The Multiobjective Traveling Salesman Problem: A Survey and a New Approach

    • Thibaut Lust, Jacques Teghem
    Pages 119-141

  8. On the Performance of Local Search for the Biobjective Traveling Salesman Problem

    • Luís Paquete, Thomas Stützle
    Pages 143-165

  9. A Bi-objective Metaheuristic for Disaster Relief Operation Planning

    • Pamela C. Nolz, Karl F. Doerner, Walter J. Gutjahr, Richard F. Hartl
    Pages 167-187

  10. Back Matter

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Keywords

About this book

The purpose of this book is to collect contributions that deal with the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems. Such a collection intends to provide an overview of the state-of-the-art developments in this field, with the aim of motivating more researchers in operations research, engineering, and computer science, to do research in this area. As such, this book is expected to become a valuable reference for those wishing to do research on the use of nature inspired metaheuristics for solving multi-objective combinatorial optimization problems.

Editors and Affiliations

  • Depto. de Computación, CINVESTAV-IPN, México, Mexico

    Carlos A. Coello Coello

  • Parc scientifique de la Haute-Borne, LIFL/CNRS/Polytech’Lille/INRIA, Villeneuve d’Ascq, France

    Clarisse Dhaenens

  • Parc scientifique de la Haute-Borne, INRIA/LIFL/CNRS, Villeneuve d’Ascq, France

    Laetitia Jourdan

Bibliographic Information

  • Book Title: Advances in Multi-Objective Nature Inspired Computing

  • Editors: Carlos A. Coello Coello, Clarisse Dhaenens, Laetitia Jourdan

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-11218-8

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2010

  • Hardcover ISBN: 978-3-642-11217-1Published: 04 February 2010

  • Softcover ISBN: 978-3-642-26238-8Published: 04 May 2012

  • eBook ISBN: 978-3-642-11218-8Published: 29 December 2009

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XV, 195

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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