引用本文:郭文艳,王远,戴芳,等.基于精英混沌搜索策略的交替正余弦算法[J].控制与决策,2019,34(8):1654-1662
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基于精英混沌搜索策略的交替正余弦算法
郭文艳,王远,戴芳,刘婷
(西安理工大学理学院,西安710054)
摘要:
正余弦算法是一种新的基于种群的随机寻优方法,利用正余弦函数使解震荡性地趋于全局最优解,其线性调整策略及较弱的局部搜索能力严重地影响了算法的性能.为了提高正弦余弦算法的计算精度,提出基于精英混沌搜索策略的交替正余弦算法.新算法采用基于对数曲线的非线性调整策略修改控制参数,利用精英个体的混沌搜索策略增强算法的开发能力,并将基于该策略的正余弦算法与反向学习算法交替执行增强算法的探索能力,降低算法的时间复杂度,提高算法的收敛速度.对23个基准测试函数进行仿真实验,与改进的正余弦算法以及最新的基于启发式的算法进行比较,深入的参数实验分析以及比较结果验证了所提出算法的有效性,统计分析证实了所提出算法的优越性.
关键词:  正余弦算法  混沌搜索  非线性策略  反向学习  粒子群优化  灰狼优化
DOI:10.13195/j.kzyjc.2018.0006
分类号:TP301.6
基金项目:国家自然科学基金项目(61772416,11601419).
Alternating sine cosine algorithm based on elite chaotic search strategy
GUO Wen-yan,WANG Yuan,DAI Fang,LIU Ting
(School of Science,Xián University of Technology,Xián710054,China)
Abstract:
The sine cosine algorithm(SCA) is a new population-based stochastic optimization method. It uses sine and cosine functions to fluctuate the solution run to the global optimal solution. Its linear adjustment strategy and weak local search ability seriously affect the performance of the algorithm. In order to improve the calculation accuracy of the sine cosine algorithm, an alternating sine cosine algorithm based on the elite chaotic search strategy is proposed, which uses the nonlinear adjustment strategy based on logarithmic curve to modify the control parameters, uses the elite individuals' chaotic search strategy to enhance the exploitation ability of the algorithm. The SCA based on this strategy and the opposition-based learning algorithm are alternately implemented to enhance the exploration ability, reduce the time complexity and improve the convergence speed of the algorithm. The proposed method has been tested by 23 benchmark test functions, and compared with the improved SCA and the state-of-the-art heuristic algorithm. The comprehensive parameter experiment and results analysis show the effectiveness and superiority of the proposed algorithm.
Key words:  sine cosine algorithm  chaotic search  nonlinear strategy  opposition-based learning  particle swarm optimization  grey wolf optimization

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