柯西变异的混沌自适应被囊群算法

Chaos Adaptive Tunicate Swarm Algorithm Based on Cauchy Mutation

针对被囊群算法(TSA)收敛速度慢,寻优精度低,易陷入局部极值等问题,提出了基于柯西变异的混沌自适应被囊群算法(KZCTSA).首先,采用Circle混沌初始化整个被囊种群,提高种群多样性,提升算法全局搜索能力;其次,引入自适应权重调整算法参数分配,平衡算法全局寻优和局部开拓能力;最后,使用柯西变异协调算法跳出局部最优能力.通过在10个基准测试函数上与其他算法比较寻优结果,并进行Wilcoxon、Fiedeman秩和检验评价算法性能,结果表明KZCTSA具有更好的求解精度和收敛速度.

Aiming at the problems of slow convergence speed,low optimization accuracy and easy to fall into local extremum of tunicate swarm algorithm(TSA),a chaotic adaptive tunicate swarm algorithm based on Cauchy mutation(KZCTSA)is proposed.Firstly,the whole tunicate population is initialized by circle chaos to improve the diversity of the population and the global search ability of the algorithm;Secondly,the parameter allocation of adaptive weight adjustment algorithm is introduced to balance the global optimization and local development ability of the algorithm;Finally,the Cauchy mutation coordination algorithm is used to jump out of the local optimal ability.By comparing the optimization results with other algorithms on 10 benchmark functions,and evaluating the performance of the algorithm by Wilcoxon and Fieldman rank sum test,the results show that KZCTSA has better solution accuracy and convergence speed.