Biased Bi-Population Evolutionary Algorithm for Energy-Efficient Fuzzy Flexible Job Shop Scheduling with Deteriorating Jobs

作     者：Libao Deng Yingjian Zhu Yuanzhu Di Lili Zhang 

作者机构：School of Information Science and EngineeringHarbin Institute of TechnologyWeihai 264209China. Department of Computer ScienceMaynooth UniversityMaynoothW23 F2H6 the School of ComputingDublin City UniversityDublinD09 V209Ireland. 

出 版 物：《Complex System Modeling and Simulation》 (复杂系统建模与仿真（英文）)

年 卷 期：2024年第4卷第1期

页      面：15-32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）] 

主　　题：bi-population evolutionary algorithm Q-learning algorithm fuzzy deteriorating effect energy flexible job shop scheduling 

摘      要：There are many studies about flexible job shop scheduling problem with fuzzy processing time and deteriorating scheduling,but most scholars neglect the connection between them,which means the purpose of both models is to simulate a more realistic factory *** this perspective,the solutions can be more precise and practical if both issues are considered ***,the deterioration effect is treated as a part of the fuzzy job shop scheduling problem in this paper,which means the linear increase of a certain processing time is transformed into an internal linear shift of a triangle fuzzy processing *** from that,many other contributions can be stated as follows.A new algorithm called reinforcement learning based biased bi-population evolutionary algorithm(RB2EA)is proposed,which utilizes Q-learning algorithm to adjust the size of the two populations and the interaction frequency according to the quality of population.A local enhancement method which combimes multiple local search stratgies is *** interaction mechanism is designed to promote the convergence of the *** experiments are designed to evaluate the efficacy of RB2EA,and the conclusion can be drew that RB2EA is able to solve energy-efficient fuzzy flexible job shop scheduling problem with deteriorating jobs(EFFJSPD)efficiently.