论文信息 - Simple Genetic Algorithm with Local Tuning: Efficient Global Optimizing Technique

Simple Genetic Algorithm with Local Tuning: Efficient Global Optimizing Technique

Genetic algorithms are known to be efficient for global optimizing. However, they are not well suited to perform finely-tuned local searches and are prone to converge prematurely before the best solution has been found. This paper uses genetic diversity measurements to prevent premature convergence and a hybridizing genetic algorithm with simplex downhill method to speed up convergence. Three case studies show the procedure to be efficient, tough, and robust.

I. Douglas | R. Yang

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