计算机科学 ›› 2014, Vol. 41 ›› Issue (6): 254-259.doi: 10.11896/j.issn.1002-137X.2014.06.050
葛宇,梁静,王学平,谢小川
GE Yu,LIANG Jing,WANG Xue-ping and XIE Xiao-chuan
摘要： 针对多目标连续优化问题,依据人工蜂群算法原理给出其求解流程,并指出算法中更新策略存在盲目搜索和丢失优秀个体的不足,随后提出改进方案。改进方案包含两部分:首先,设计一种自适应搜索算子,使算法在运行过程中能根据个体质量自动调节搜索范围,让算法搜索行为准确高效；其次,利用外部集合记录下新产生的个体,一次迭代完成后结合外部集合重新构造种群,让算法能有效地保存进化过程中产生的优秀个体。实验中将改进人工蜂群算法与NSGA2算法、改进前算法以及文献报道的同类优秀算法进行了比较,结果说明:改进人工蜂群算法在求解多目标连续优化问题中具有良好的收敛性和均匀性。
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