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This paper proposes a kind of evolutionary parallel local search technique (EPLS) that integrates the reproduction mechanisms from evolutionary algorithms and simplex method. The major aim is to explore the tradeoff between exploration and exploitation for optimizing multimodal functions. It has been cost-efficiently reached by means of parallel local(More)
A method of predicting Pareto dominance in multi-objective optimization using pattern recognition, and the framework of Pareto dominance classifier are proposed. A kind of Bayesian classifier is preliminarily implemented. It is used to predict Pareto dominance among the candidate solutions for various typical multi-objective optimization problems. The(More)
In order to further ease the disaster of computing costs in multi-objective optimization problem, we've put forward a kind of multi-objective genetic algorithm based on clustering. The algorithm uses the fuzzy c-means clustering control the similar individuals gathered in a class and for each class construct non-dominated set with arena's principle, so that(More)
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