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Evolutionary Algorithms for Solving Multi-Objective Problems

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Evolutionary Algorithms for Solving Multi-Objective Problems Synopsis

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.

About This Edition

ISBN: 9781489994608
Publication date:
Author: Carlos Coello Coello, Gary B Lamont, David A van Veldhuizen
Publisher: Springer an imprint of Springer US
Format: Paperback
Pagination: 800 pages
Series: Genetic and Evolutionary Computation
Genres: Computer programming / software engineering
Stochastics
Probability and statistics
Optimization
Algorithms and data structures
Mathematical theory of computation
Artificial intelligence