"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 | Publication Date:2007-09-18 | ISBN:0387332545 | 800 Pages | PDF | 9 MB
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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