Parallel discrete lion swarm optimization algorithm for solving traveling salesman problem

作     者：ZHANG Daoqing JIANG Mingyan ZHANG Daoqing;JIANG Mingyan

作者机构：School of Information Science and EngineeringShandong UniversityQingdao 266237China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2020年第31卷第4期

页      面：751-760页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 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：supported by the National Natural Science Foundation of China(61771293) the Key Project of Shangdong Province(2019JZZY010111) 

主　　题：discrete lion swarm optimization(DLSO)algorithm complete 2-opt(C2-opt)algorithm parallel discrete lion swarm optimization(PDLSO)algorithm traveling salesman problem(TSP) 

摘      要：As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search *** in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is *** PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time.