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.
ISBN: | 9781489994608 |
Publication date: | 28th October 2014 |
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 |