计算机科学 ›› 2022, Vol. 49 ›› Issue (5): 212-220.doi: 10.11896/jsjkx.210300019
李浩东1, 胡洁1, 范勤勤1,2
LI Hao-dong1, HU Jie1, FAN Qin-qin1,2
摘要： 基于分区搜索的多模态多目标优化属于一种决策空间分解策略,因此它具有天然的并行性。为提高求解效率,提出了一种并行分区搜索(Parallel Zoning Search,PZS)方法来辅助多模态多目标进化算法。在PZS中,首先将多模态多目标优化问题的整个决策空间划分为多个子空间,然后利用并行计算技术来实现选定的多模态多目标进化算法在各个子区域内进行并行搜索,最后将所有子空间得到的解集进行合并和选择。为验证所提方法的有效性,文中设计了两组实验:1)在所有对比算法的运行时间相同的条件下进行实验;2)在所有对比算法的函数评价次数相同的条件下进行实验。结果表明,在计算时间相同的情况下,所提方法能够有效提高选定的多模态多目标进化算法在决策空间中所得解集的质量;而在相同函数评价次数条件下,其能够节省计算时间。文中还将与PZS相结合的多模态多目标进化算法用于求解考虑碳排放的海铁联运能耗多模态多目标优化问题,所得结果可以为海铁联运中的环境保护和运输时间问题提供决策支持。
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