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In multi-objective evolutionary optimization, maintaining a good balance between convergence and diversity is particularly crucial to decision makers, especially when tackling problems with complicated Pareto sets. According to the analysis of dominance-based and decomposition-based selection mechanisms in multi-objective evolutionary algorithms, a multi-objective evolutionary algorithm based on the...
Proximity and diversity are two basic issues in multi-objective optimization problems. However, it is hard to optimize them simultaneously, especially when tackling problems with complicated Pareto fronts and Pareto sets. To make a better performance of multi-objective optimization evolutionary algorithm, the environmental information and history information are used to generate better offsprings...
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