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中文摘要：
为高效求解多目标组合优化问题,提出一种进化计算与局部搜索结合的多目标算法。此算法基于个体排序数和密度值进行适应度赋值,采用非劣解并行局部搜索策略,在解的适应度赋值和局部搜索过程中使用Pa-reto支配的概念。实验结果表明,新算法不仅提高了优化搜索的效率,且能够找到更多的近似Pareto最优解。
英文摘要：
To efficiently solve multi-objective combinatorial optimization problems, combining evolutionary computation with local search, this paper proposed a hybrid genetic algorithm. It evaluatd the indivi-dual fitness based on the rank of the individual and its density value, used a Pareto parallel local search strategy. Used the concept of Pareto dominance to assign fitness to the solutions and in the local search procedure. The experimental results show that the proposed algorithm can improve search efficiency of optimization and find more approximate Pareto optimal solutions.
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