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© 2004

Multiobjective Optimization

Principles and Case Studies

Textbook

Part of the Decision Engineering book series (DECENGIN)

Table of contents

  1. Front Matter
    Pages I-12
  2. Principles of multiobjective optimization methods

    1. Front Matter
      Pages 13-13
    2. Yann Collette, Patrick Siarry
      Pages 15-43
    3. Yann Collette, Patrick Siarry
      Pages 45-75
    4. Yann Collette, Patrick Siarry
      Pages 77-98
    5. Yann Collette, Patrick Siarry
      Pages 99-107
    6. Yann Collette, Patrick Siarry
      Pages 109-134
    7. Yann Collette, Patrick Siarry
      Pages 135-173
  3. Evaluation of methods, and criteria for choice of method

    1. Front Matter
      Pages 175-175
    2. Yann Collette, Patrick Siarry
      Pages 177-196
    3. Yann Collette, Patrick Siarry
      Pages 197-211
    4. Yann Collette, Patrick Siarry
      Pages 213-225
  4. Case studies

    1. Front Matter
      Pages 227-227
    2. Yann Collette, Patrick Siarry
      Pages 229-235
    3. Yann Collette, Patrick Siarry
      Pages 237-250
    4. Yann Collette, Patrick Siarry
      Pages 251-267
    5. Yann Collette, Patrick Siarry
      Pages 269-270
  5. Back Matter
    Pages 271-293

About this book

Introduction

From whatever domain they come, engineers are faced daily with optimization problems that requires conflicting objectives to be met. This monograph systematically presents several multiobjective optimization methods accompanied by many analytical examples. Each method or definition is clarified, when possible, by an illustration. Multiobjective Optimization treats not only engineering problems, e.g in mechanics, but also problems arising in operations research and management. It explains how to choose the most suitable method to solve a given problem and uses three primary application examples: optimization of the numerical simulation of an industrial process; sizing of a telecommunication network; and decision-aid tools for the sorting of bids. This book is intended for engineering students, and those in applied mathematics, algorithmics, economics (operational research), production management, and computer scientists.

Keywords

algorithm algorithmics algorithms communication fuzzy metaheuristic multi-objective optimization operations research optimization simulation

Authors and affiliations

  1. 1.ChellesFrance
  2. 2.L.E.R.I.S.S.Université de Paris XIICréteilFrance

Bibliographic information

Reviews

From the reviews:

"Multiobjective optimization allows a degree of freedom, which is lacking in mono-objective optimization. … The book is accessible to the novice and expert … and can be used by students, engineers and scientists working in aerospace, automotive, and mechanical and civil engineering." (Stefan Jendo, Zentralblatt MATH, Vol. 1103 (5), 2007)