蟻の理論を用いた遺伝的アルゴリズムの環境変化の考察
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概要
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Genetic Algorithms (GA) is applied to search an optimalor near-optimal solution by imitating the biological evolution.In GA, all individuals in a population tend to converge to an optimalpoint. Once it converges, the conventional GA is difficult to adaptitself in changing environments. In nature, it has been found thatin each worker ant colony, about 20% are diligent worker ants, 60%are ordinary, and 20% are lazy. That is 20:60:20 rule. We haveapplied this rule to preserve not only the best individuals but alsothe poorest ones. Simulation results verified that the poorest individualscontribute to dealing with optimization problems in changing environments.
- 2008-12-19