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In this study, we consider the scenario that differential evolution (DE) is applied for global numerical optimization and the index-based neighborhood information of population is used for enhancing the performance of DE. Although many methods are developed under this scenario, neighborhood information of current population has not been systematically exploited in the DE algorithm design. Furthermore,...
In most differential evolution (DE) algorithms, little work for the design of the mutation operator is directly relevant to the information of fitness landscape of the problem being solved. As the previous studies show, different mutation strategies are suitable for different problems with different fitness landscapes, and the performance of the mutation strategy is tightly linked to the fitness landscape...
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