| Evolutionary Algorithms for Solving Multi-Objective Problems Contributor(s): Coello Coello, Carlos (Author), Lamont, Gary B. (Author), Van Veldhuizen, David A. (Author) |
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ISBN: 0387332545 ISBN-13: 9780387332543 Publisher: Springer OUR PRICE: $123.49 Product Type: Hardcover - Other Formats Published: September 2007 Annotation: 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. |
| Additional Information |
| BISAC Categories: - Computers | Computer Science - Computers | Intelligence (ai) & Semantics - Mathematics | Linear & Nonlinear Programming |
| Dewey: 004.015 |
| LCCN: 2007930239 |
| Series: Genetic and Evolutionary Computation |
| Physical Information: 1.67" H x 6.48" W x 9.25" (2.87 lbs) 824 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |