典型文献
An Improved Tunicate Swarm Algorithm with Best-random Mutation Strategy for Global Optimization Problems
文献摘要：
The Tunicate Swarm Algorithm(TSA)inspires by simulating the lives of Tunicates at sea and how food is obtained.This algorithm is easily entrapped to local optimization despite the simplicity and optimal,leading to early convergence compared to some metaheuristic algorithms.This paper sought to improve this algorithm's performance using mutating operators such as the lévy mutation operator,the Cauchy mutation operator,and the Gaussian mutation operator for global optimization problems.Thus,we introduced a version of this algorithm called the QLGCTSA algorithm.Each of these operators has a different performance,increasing the QLGCTSA algorithm performance at a specific optimization operation stage.This algo-rithm has been run on benchmark functions,including three different compositions,unimodal(UM),and multimodal(MM)groups and its performance evaluate six large-scale engineering problems.Experimental results show that the QLGCTSA algorithm had outperformed other competing optimization algorithms.
文献关键词：
中图分类号：
作者姓名：
Farhad Soleimanian Gharehchopogh
作者机构：
Department of Computer Engineering,Urmia Branch,Islamic Azad University,Urmia,Iran
文献出处：
引用格式：
[1]Farhad Soleimanian Gharehchopogh-.An Improved Tunicate Swarm Algorithm with Best-random Mutation Strategy for Global Optimization Problems)[J].仿生工程学报（英文版）,2022(04):1177-1202
A类：
Tunicate,Tunicates,mutating,QLGCTSA
B类：
An,Improved,Swarm,Algorithm,Best,random,Mutation,Strategy,Global,Optimization,Problems,inspires,by,simulating,lives,sea,food,obtained,This,easily,entrapped,local,optimization,despite,simplicity,optimal,leading,early,convergence,compared,some,metaheuristic,algorithms,paper,sought,improve,this,performance,using,operators,such,vy,mutation,Cauchy,Gaussian,global,problems,Thus,we,introduced,version,called,Each,these,has,different,increasing,specific,operation,stage,been,run,benchmark,functions,including,three,compositions,unimodal,UM,multimodal,MM,groups,its,evaluate,six,large,scale,engineering,Experimental,results,show,that,had,outperformed,other,competing
AB值：
0.59562
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
