1(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)2(Yunnan Key Laboratory of Computer Technology Applications,Kunming 650500,China)
Abstract：The beetle antenna search algorithm(BAS)has the characteristics of fast search and simple execution,but it is easy to fall into the local extremum in the optimization of multi-peak complex function.The global search ability of genetic algorithm(GA)is strong,but the convergence speed is slow and the convergence accuracy is not high.Based on the advantages and disadvantages of the above two algorithms,this paper proposes an new optimization algorithm by mixing BAS and GA.Firstly,the multi-directional exploration feedback strategy is designed to increase the search ability of the BAS algorithm,and then the BAS algorithm is embedded in GA to obtain better solution in a short time,thus speeding up the global convergence speed of GA.In addition,the extended crossover operator and adaptive parameter adjustment method are used in GA to maintain the diversity of the population,which is helpful to avoid the local extreme problem and further improve the optimization performance.According to the optimization results of the test functions,the proposed hybrid algorithm has higher convergence accuracy and optimization performance than other hybrid algorithms.
2020, Vol. 41 
