Genetic Algorithms in Search, Optimization and Machine Learning

Description

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 orgenetics is assumed.

Table of Contents

1. Foreword
2. Preface
3. A Gentle Introduction to Genetic Algorithms
4. Genetic Algorithms Revisited: Mathematical Foundations
5. Computer Implementation of a Genetic Algorithm
6. Some Applications of Genetic Algorithms
7. Advanced Operators and Techniques in Genetic Search
8. Introduction to Genetics-Based Machine Learning
9. Applications of Genetics-Based Machine Learning
10. A Look Back, A Glance Ahead
11. Appendices:
12. A Review of Combinatorics and Elementary Probability
13. Pascal with Random Number Generation for Fortran, Basic, and Cobol Programmers
14. A Simple Genetic Algorithm
15. A Simple Classifier System (SCS) in PASCAL
16. Partition Coefficient Transforms for Problems-Coding Analysis
17. Bibliography
18. Index

Author Biography

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.