Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the travelin
Genetic Algorithms + Data Structures = Evolution Programs
โ Scribed by Zbigniew Michalewicz (auth.)
- Publisher
- Springer Berlin Heidelberg
- Year
- 1994
- Tongue
- English
- Leaves
- 344
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Front Matter....Pages I-XVI
Introduction....Pages 1-10
Front Matter....Pages 11-11
GAs: What Are They?....Pages 13-30
GAs: How Do They Work?....Pages 31-42
GAs: Why Do They Work?....Pages 43-53
GAs: Selected Topics....Pages 55-91
Front Matter....Pages 93-93
Binary or Float?....Pages 95-104
Fine Local Tuning....Pages 105-118
Handling Constraints....Pages 119-166
Evolution Strategies and Other Methods....Pages 167-184
Front Matter....Pages 185-185
The Transportation Problem....Pages 187-209
The Traveling Salesman Problem....Pages 211-237
Drawing Graphs, Scheduling, Partitioning, and Path Planning....Pages 239-269
Machine Learning....Pages 271-285
Conclusions....Pages 287-308
Back Matter....Pages 309-340
โฆ Subjects
Artificial Intelligence (incl. Robotics); Algorithms; Numerical Analysis; Programming Techniques; Software Engineering; Operation Research/Decision Theory
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Zbigniew Michalewicz's Genetic Algorithms + Data Structures = Evolution Programs has three sections. The first section is a straightforward introduction to genetic algorithms. In the second section, Michalewicz describes how to apply genetic algorithms to numerical optimization. Michalewicz, who is