摘要
针对基本状态转移算法(state transition algorithm,STA)搜索效率低和后期收敛速度慢的不足,对不同算子求解特定优化问题的效果差异性展开统计研究,提出一种带有策略自适应的状态转移算法(SaSTA).首先,定义成功率和下降率两个指标,并在3个测试函数上进行统计研究,以证明不同算子对算法搜索能力的影响,设计一种综合成功率和下降率的评价指标对最优算子进行自适应选择;然后,采用一种非线性控制参数策略平衡算法的探索和开发能力;最后,将所提出算法应用于15个基准测试函数(100维、300维和500维).仿真结果表明,所提出算法在求解精度、收敛速度和稳定性方面均明显优于其他对比算法.
In view of the shortcomings of basic state transition algorithm(STA)such as slow search efficiency and low convergence accuracy in the later search stage,based on the statistical study of the difference of the effects of different operators in solving specific optimization problems,a state transition algorithm with strategy adaptation(SaSTA)is proposed.Firstly,two indexes of success rate and descent rate are defined,and statistical studies are conducted on three test functions to prove the influence of different operators on the search capability of the algorithm,and an evaluation index of comprehensive success rate and descent rate is designed to adaptively select the optimal operator.Then,a nonlinear control parameter strategy is adopted to balance the exploration and exploitation ability of the algorithm.Finally,the proposed algorithm is applied to 15 benchmark functions(100,300 and 500 dimension).The simulation results show that the proposed algorithm is superior to other comparative algorithms in terms of solution precise,convergence speed and stability.
作者
董颖超
张宏立
王聪
DONG Ying-chao;ZHANG Hong-li;WANG Cong(College of Electrical Engineering,Xinjiang University,Urumqi 830047,China)
出处
《控制与决策》
EI
CSCD
北大核心
2022年第3期574-582,共9页
Control and Decision
基金
国家自然科学基金项目(51767022,51967019)。
关键词
状态转移算法
元启发式
策略自适应
统计研究
全局优化
state transition algorithm
metaheuristic
strategy adaptation
statistical study
global optimization
