Chaotic Local Search-Based Differential Evolution Algorithms for Optimization

作     者：Gao, Shangce Yu, Yang Wang, Yirui Wang, Jiahai Cheng, Jiujun Zhou, MengChu 

作者机构：Univ Toyama Fac Engn Toyama 9308555 Japan Sun Yat Sen Univ Dept Comp Sci Guangzhou 510275 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Comp Minist Educ Shanghai 200092 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS》 (IEEE Trans. Syst. Man Cybern. Syst.)

年 卷 期：2021年第51卷第6期

页      面：3954-3967页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China [61673403, 61872271] Japan Society for the Promotion of Science KAKENHI [JP17K12751] 

主　　题：Optimization Chaos Convergence Sociology Statistics Logistics Search problems Chaotic local search (CLS) chaotic map differential evolution (DE) incorporation scheme optimization algorithm 

摘      要：JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in comparison with other evolutionary optimization algorithms. However, it suffers from the premature convergence problem and is easily trapped into local optima. This article presents a novel JADE variant by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem. Taking advantages of the ergodicity and nonrepetitious nature of chaos, it can diversify the population and thus has a chance to explore a huge search space. Because of the inherent local exploitation ability, its embedded CLS can exploit a small region to refine solutions obtained by JADE. Hence, it can well balance the exploration and exploitation in a search process and further improve its performance. Four kinds of its CLS incorporation schemes are studied. Multiple chaotic maps are individually, randomly, parallelly, and memory-selectively incorporated into CLS. Experimental and statistical analyses are performed on a set of 53 benchmark functions and four real-world optimization problems. Results show that it has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.