Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolut

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

By Carlos A. Coello Coello, Gary B. Lamont, David A. Van Veldhuizen,

Publisher: Springer
Number Of Pages: 800
Publication Date: 2007-09-18
Sales Rank: 700544
ISBN / ASIN: 0387332545
EAN: 9780387332543
Binding: Hardcover
Manufacturer: Springer
Studio: Springer

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.

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