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9780387332543

Evolutionary Algorithms for Solving Multi-objective Problems

by ; ;
  • ISBN13:

    9780387332543

  • ISBN10:

    0387332545

  • Edition: 2nd
  • Format: Hardcover
  • Copyright: 2007-09-07
  • Publisher: Springer-Nature New York Inc
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Summary

Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems. This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.

Table of Contents

List of Figures
List of Tables
Preface
Foreword
Basic Concepts
Evolutionary Algorithm MOP Approaches
MOEA Test Suites
MOEA Testing and Analysis
MOEA Theory and Issues
Applications
MOEA Parallelization
Multi-Criteria Decision Making
Special Topics
Epilog
MOEA Classification and Technique Analysis
MOPs in the Literature
Ptrue & PFtrue for Selected Numeric MOPs
Ptrue & PFtrue for Side-Constrained MOPs
MOEA Software Availability
MOEA-Related Information
Index
References
Table of Contents provided by Publisher. All Rights Reserved.

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