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MOEAs Based on Dynamic Chaotic Mutation

In reality, there are varieties of practical problems which are all optimizing many objectives at the same time. Meanwhile, these problems are usually highly complex, which are called multi-objective optimization problem. Multi-Objective Evolutionary Algorithms, shorted as MOEAs, is very suitable for solving this kind of problem. Chaos is defined as a random phenomenon with a sensitive dependence on initial conditions, which is produced by deterministic system. It covers almost each branch of both natural science and social science. The main work of this paper is to analyze and make conclusion about the dynamic chaotic mutation and MOEAs. Based on it, this paper proves the convergence of dynamic chaos multi-objective optimization, and proposes MOEAs based on dynamic chaotic mutation.