An Evolved Dispatching Rule Based Scheduling Approach for Solving DJSS Problem
作者单位：Key Laboratory of Electric Drive and Control of Anhui Higher Education Institutes Anhui Polytechnic University School of Electrical Engineering Anhui Polytechnic University
会议名称：《第40届中国控制会议》
会议日期：2021年
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)] 08[工学] 081104[工学-模式识别与智能系统] 0802[工学-机械工程] 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）]
关 键 词：Dispatching Rule Genetic Programming Dynamic Job Shop Scheduling Combinatorial Optimization
摘 要：Dynamic job shop scheduling（DJSS） has been shown as a realistic and complex combinatorial optimization problem, which is characterized by complexity, dynamics, and uncertainty. Though dispatching rules（DRs） have been seen as a suitable method for solving DJSS problem, it is hard to manually design a DR with good scheduling performance considering all the aspects, much less a general DR for the complex dynamic environment of the job shop. This paper presents a genetic programming hyper-heuristic（GPHH） based DR evaluation approach to automatically generate customized DRs, in which job shop configuration, objective, and other information are considered. After testing it on the single objective DJSS problems with six different scenarios, the experimental result indicates that the proposed method can effectively evolve better DRs for different DJSS problems than manually designed DRs. Besides, the role of four key parameters in GPHH, including the number of generations, the population size, and the maximal depth, have been deeply analyzed based on the corresponding experiments.