摘要
针对目前多种群算法解决动态优化问题时存在过多冗余计算、寻优精度低等缺陷,提出多种群串行搜索的引力搜索算法。采用多种群串行搜索的策略,便于当前子种群利用其他已收敛种群的进化信息。为解决多峰重复搜索而带来的冗余计算问题,提出具有约束条件的初始化策略,给予初始化的粒子以方向性的指引,避免其初始化在已寻峰区域;采用距离判决的策略发现并终止多峰重复搜索。为全面的监测环境变化及解决多样性丢失问题,提出一种监测环境策略及追踪策略。研究结果表明:所提算法,面对不同的环境变化程度以及不同的峰值数量,其求解精度都优于其他7种对比算法的求解精度,证明该算法在求解动态优化问题上的优越性。
To improve the redundant computing and low accuracy of solving dynamic optimization problems（DOPs） for multi-population algorithm, a novel improved multi-population gravitational search algorithm（IMGSA） was proposed. In IMGSA, the multi-population serial strategy was good for the present subpopulation to use evolutionary information of convergence population. A constraint initialization strategy was proposed to reduce the redundant computing which was generated by multiple populations searching repeatedly. Simultaneously, a distance decision strategy was used to stop multiple populations searching. Eventually, a monitoring and tracking strategy was used to monitor the environmental change and track the local peaks. The results show that IMGSA has a better performance in solving DOPs than those of other seven dynamic algorithms in different degree of environmental change or different peak number. It can prove the validity of proposed algorithm.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第9期3325-3331,共7页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61175126)
中央高校基本科研业务费专项资金资助项目(HEUCFZ1209)
高等学校博士学科点专项科研基金项目资助课题(20112304110009)
黑龙江省博士后基金资助项目(LBH-Z12073)
辽宁省教育厅科学研究一般项目(L2012458)
辽宁省博士科研启动基金资助项目(20120511)~~
