Evolutionary Algorithms for Solving Multi-Objective Problems - Carlos A. Coello

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. TOC: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.- Appendix A: MOEA Classification and Technique Analysis.- Appendix B: MOPs in the Literature.- Appendix C: Ptrue and PFtrue for Selected Numberic MOPs.- Appendix D: Ptrue and PFtrue for Side-constrained MOPs.- Appendix E: MOEA Software Availability.- Appendix F: MOEA-Related Information.

Tytuł: Evolutionary Algorithms for Solving Multi-Objective Problems
Autor:

Carlos A. Coello

Seria: Genetic and Evolutionary Computation
Data wydania: październik 2007
Wydawca: Springer-Verlag GmbH
ISBN: 0387332545
EAN: 9780387332543
Wymiary: 244 x 165 x 42