计算机科学 ›› 2016, Vol. 43 ›› Issue (12): 241-247.doi: 10.11896/j.issn.1002-137X.2016.12.044
刘敏,曾文华,刘玉珍
LIU Min, ZENG Wen-hua and LIU Yu-zhen
摘要: 如何利用过去搜索到的最优解对新的环境变化做出快速响应,是动态进化多目标优化(Dynamic Evolutio-nary Multi- objective Optimization,DEMO)研究的一大挑战。为此提出了一种串式记忆(Bunchy Memory,BM)方法。设计了基于极小化效应函数的抽取过程,从非支配集中抽取一串记忆串,以便保持记忆的多样性;将记忆体组织成串式队列的方式,以便将过去数次环境变化下抽取的记忆串存入记忆体;提出了基于二进制锦标赛选择的检索过程以复用记忆体中过去的最优解,来快速响应新的变化。BM方法具有良好的记忆效果,显著地提高了DEMO算法的收敛性和多样性。4个标准测试问题上的实验结果表明,BM方法比其它3种方法具有更好的记忆能力。相应地,集成了BM方法的DEMO算法所获得解集的收敛性与多样性也明显好于其它3种DEMO算法。
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