摘要
基于对混沌算法、遗传算法和禁忌搜索法的比较分析,结合实际无功优化问题提出了一种引入改进tent映射的遗传禁忌混合算法,它以遗传种群为进化主体,同时伴随tent映射产生辅助个体,在状态更新中通过一定的选择比较机制引入辅助个体,在进化过程中综合禁忌搜索操作,一定程度上避免了迂回搜索。将其应用于某地区电网无功优化中,通过与基本遗传算法、改进遗传算法和遗传禁忌算法的比较表明该混合算法性能更为优良。
Based on the comparison and analysis of properties and hybrid strategies of genetic （GA）, tabu search （TS） and chaotic （COA） algorithm, the paper proposes a new hybrid algorithm named genetic-tabu search hybrid algorithm with improved tent map （TFGA）. Improved GA is the main part of the hybrid algorithm, and auxiliary individuals are formed by the means of the iteration of improved tent map which is used to optimize population by an introduction mechanism. Moreover, tabu search operation is used in combination with population evolutionary so that circuitous search path can be avoided partly. The resuhs of reactive power optimization in the local grid showed that the hybrid algorithm proposed in the paper has better ability of searching optima compared with GA, improved CA and GA/TS hybrid algorithm.
出处
《陕西电力》
2012年第11期1-7,共7页
Shanxi Electric Power
基金
国家自然科学基金资助项目(51177117)
高等学校博士学科点专项科研基金资助项目(20100201110023)
关键词
无功优化
遗传禁忌混合算法
改进tent映射
reactive power optimization
genetic-tabu search hybrid algorithm
improved tent map
