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A New Multi-objective Differential Evolution Algorithm

机译:一种新的多目标差分进化算法

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A new multi-objective differential evolution algorithm is proposed. A dual elitist selection strategy based on Individual Pareto Rank and Individual Density is employed in the proposed new algorithm. It also remains the characteristic of keeping elitists. The corresponding effects comparisons of new algorithm with other classic multi-objective evolutionary algorithms show that new algorithm require initial population small in size, fewer iterations, and output more optimal solutions. It can improve the diversity metric significantly while ensuring satisfactory convergence metric.
机译:提出了一种新的多目标差分进化算法。该算法采用了基于个体帕累托等级和个体密度的双重精英选择策略。这也仍然是保持精英人士的特征。新算法与其他经典的多目标进化算法的相应效果比较表明,新算法要求初始种群的规模小,迭代次数少,并输出更多的最优解。它可以在确保令人满意的收敛指标的同时,显着提高分集指标。

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