Evolutionary Algorithms

Ioannis T. Christou, Wayne Martin, Robert R. Meyer (auth.), Lawrence David Davis, Kenneth De Jong, Michael D. Vose, L. Darrell Whitley (eds.)9780387988269, 0387988262

This IMA Volume in Mathematics and its Applications EVOLUTIONARY ALGORITHMS is based on the proceedings of a workshop that was an integral part of the 1996-97 IMA program on “MATHEMATICS IN HIGH-PERFORMANCE COMPUTING.” I thank Lawrence David Davis (Tica Associates), Kenneth De Jong (Computer Science, George Mason University), Michael D. Vose (Computer Science, The University of Tennessee), and L. Darrell Whitley (Computer Science, Colorado State University) for their excellent work in organizing the workshop and for editing the proceedings. Further appreciation is ex­ tended to Donald G. Truhlar (Chemistry and Supercomputing Institute, University of Minnesota) who was also one of the workshop organizers. In addition, I also take this opportunity to thank the National Science Foundation (NSF), Minnesota Supercomputing Institute (MSI), and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr., Professor and Director v PREFACE The IMA Workshop on Evolutionary Algorithms brought together many of the top researchers working in the area of Evolutionary Com­ putation for a week of intensive interaction. The field of Evolutionary Computation has developed significantly over the past 30 years and today consists a variety of subfields such as genetic algorithms, evolution strate­ gies, evolutionary programming, and genetic programming, each with their own algorithmic perspectives and goals.

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Table of contents :
Front Matter….Pages i-x
Genetic Algorithms as Multi-Coordinators in Large-Scale Optimization….Pages 1-15
Telecommunication Network Optimization with Genetic Algorithms: A Decade of Practice….Pages 17-32
Using Evolutionary Algorithms to Search for Control Parameters in a Nonlinear Partial Differential Equation….Pages 33-64
Applying Genetic Algorithms to Real-World Problems….Pages 65-88
An Overview of Evolutionary Programming….Pages 89-109
A Hierarchical Genetic Algorithm for System Identification and Curve Fitting with a Supercomputer Implementation….Pages 111-137
Experiences with the PGAPack Parallel Genetic Algorithm Library….Pages 139-149
The Significance of the Evaluation Function in Evolutionary Algorithms….Pages 151-166
Genetic Algorithm Optimization of Atomic Clusters….Pages 167-175
Search, Binary Representations and Counting Optima….Pages 177-189
An Investigation of GA Performance Results for Different Cardinality Alphabets….Pages 191-206
Genetic Algorithms and the Design of Experiments….Pages 207-226
Efficient Parameter Optimization Based on Combination of Direct Global and Local Search Methods….Pages 227-249
What are Genetic Algorithms? A Mathematical Prespective….Pages 251-276
Survey of Projects Involving Evolutionary Algorithms Sponsored by the Electric Power Research Institute….Pages 277-293
Back Matter….Pages 294-300