Solving flexible job shop scheduling problem by a multi-swarm collaborative genetic algorithm

作     者：WANG Cuiyu LI Yang LI Xinyu WANG Cuiyu;LI Yang;LI Xinyu

作者机构：School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China 

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

年 卷 期：2021年第32卷第2期

页      面：261-271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] 080202[工学-机械电子工程] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 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 Key R&D Program of China(2018AAA0101700) the Program for HUST Academic Frontier Youth Team(2017QYTD04) 

主　　题：flexible job shop scheduling problem(FJSP) collaborative genetic algorithm co-evolutionary algorithm 

摘      要：The flexible job shop scheduling problem(FJSP),which is NP-hard,widely exists in many manufacturing *** is very hard to be solved.A multi-swarm collaborative genetic algorithm(MSCGA)based on the collaborative optimization algorithm is proposed for the ***-population structure is used to independently evolve two sub-problems of the FJSP in the *** operators are adopted and designed to ensure this algorithm to achieve a good *** famous FJSP benchmarks are chosen to evaluate the effectiveness of the *** adaptability and superiority of the proposed method are demonstrated by comparing with other reported algorithms.