Genetic Algorithms in search, Optimization & Machine Learning

The text introduces the theory, operation, and application of genetic algorithms----search algorithms based on the mechanics of natural selection and genetics. This book, suitable for both course work and self-study, brings together for the first time, in an informal, tutorial fashion, the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields: programmers, scientists, engineers, mathematicians, statisticians and management scientists will all find interesting possibilities here. Major concepts are illustrated with running examples, and Pascal computer programs illustrate major algorithms. Chapter concludes with exercises and computer assignments. No prior knowledge of Gas or genetics is assumed.

About the Author

David E. Goldberg is presently Associate Professor of Engineering Mechanics at the University of Alabama. He received his Ph.D. from the University of Michigan. As a graduate student at the University of Michigan, he spearheaded a successful project applying genetic algorithms and classifier systems to the control of natural gas pipelines. He has continued his research in genetic algorithms and classifier systems, and has had 12 years of consulting experience in industry and government and has published numerous articles and papers.