Modeling GA Performance for Control Parameter Optimization

Abstract

Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control parameter optimization. We enhance this process by incorporating a neural network for tness evaluation. This neural network is trained to learn the complex interactions of the… (More)

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