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中文摘要：
为求解生产调度中的多目标混流装配线排序问题,提出一种将遗传算法与粒子群算法相结合的混合算法——GA-PSO算法.为更好地评价个体,提出一种引入个体的Pareto分级和拥挤距离的适应度函数.针对标准PSO算法求解排序问题的不足,提出了一种将实数映射成离散值的方法.在算法的历次迭代中,早期通过遗传算法全局搜索优势扩大搜索范围,抑制早期收敛;后期通过粒子群算法局部搜索加速收敛.通过基准算例分析,证明了所提算法优于SPEA-Ⅱ,NSGA-Ⅱ和PS-NC GA算法.本算法已实际应用于某企业混流装配线排序.
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