Synopsis
I. Genetic Algorithms.- 1 GAs: What Are They?.- 2 GAs: How Do They Work?.- 3 GAs: Why Do They Work?.- 4 GAs: Selected Topics.- II. Numerical Optimization.- 5 Binary or Float?.- 6 Fine Local Tuning.- 7 Handling Constraints.- 8 Evolution Strategies and Other Methods.- III. Evolution Programs.- 9 The Transportation Problem.- 10 The Traveling Salesman Problem.- 11 Drawing Graphs, Scheduling, and Partitioning.- 12 Machine Learning.- Conclusions.- References.
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