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中文摘要：
基于合作型协同进化模型，提出了一种新型的多闩标优化进化算法。该算法使用精英保留的思想以加快收敛速度，并采用一种新型的子群体间合作方式，提高了候选解的多样性。且避免了在一般多目标优化进化算法中难以处理的适应值分配或非支配排序过程，从而大大减小了计算资源的消耗。使用图形法和三种定量的测度将所提算法与一种经典的多目标优化进化算法NSGA-Ⅱ在一组标准测试函数上进行了比较，结果表明算法具有更高的搜索效率。
英文摘要：
A new multi - objective optimization evolutionary algorithm based on the model of cooperative co evolution is proposed in this paper. The algorithm incorporates the idea of elitism to motivate convergence, and adopts a novel form of collaboration between subpopulations, which improves its ability to keep diversity and avoids the difficult process of fitness assignment or non - dominance ranking in general multi - objective evolutionary algorithms so that the computational cost is greatly reduced. The proposed algorithm is compared with a well - known multi - objective evolutionary algorithm NSGA - Ⅱ on a suite of standard test functions using visual graphs and three quantitative metrics. Results indicate that this algorithm can search more effectively.
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