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Table of contents (4 chapters)
Keywords
About this book
OmeGA: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems addresses two increasingly important areas in GA implementation and practice. OmeGA, or the ordering messy genetic algorithm, combines some of the latest in competent GA technology to solve scheduling and other permutation problems. Competent GAs are those designed for principled solutions of hard problems, quickly, reliably, and accurately. Permutation and scheduling problems are difficult combinatorial optimization problems with commercial import across a variety of industries.
This book approaches both subjects systematically and clearly. The first part of the book presents the clearest description of messy GAs written to date along with an innovative adaptation of the method to ordering problems. The second part of the book investigates the algorithm on boundedly difficult test functions, showing principled scale up as problems become harder and longer. Finally, the book applies the algorithm to a test function drawn from the literature of scheduling.
Authors and Affiliations
Bibliographic Information
Book Title: OmeGA
Book Subtitle: A Competent Genetic Algorithm for Solving Permutation and Scheduling Problems
Authors: Dimitri Knjazew
Series Title: Genetic Algorithms and Evolutionary Computation
DOI: https://doi.org/10.1007/978-1-4615-0807-6
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2002
Hardcover ISBN: 978-0-7923-7460-2Published: 31 January 2002
Softcover ISBN: 978-1-4613-5249-5Published: 30 October 2012
eBook ISBN: 978-1-4615-0807-6Published: 06 December 2012
Series ISSN: 1568-2587
Edition Number: 1
Number of Pages: XXI, 152
Topics: Artificial Intelligence, Theory of Computation, Optimization