Domain Knowledge Used in Meta-Heuristic Algorithms for the Job-Shop Scheduling Problem:Review and Analysis
作者机构：State Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Department of Computer ScienceCity University of Hong KongHong KongChina
出 版 物：《Tsinghua Science and Technology》 (清华大学学报自然科学版（英文版）)
年 卷 期：2024年第29卷第5期
页 面：1368-1389页
核心收录：
学科分类：08[工学] 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(Nos.U21B2029 and 51825502)
主 题：domain knowledge job-shop scheduling problem meta-heuristic algorithm
摘 要：Meta-heuristic algorithms search the problem solution space to obtain a satisfactory solution within a reasonable *** combining domain knowledge of the specific optimization problem,the search efficiency and quality of meta-heuristic algorithms can be significantly improved,making it crucial to identify and summarize domain knowledge within the *** this paper,we summarize and analyze domain knowledge that can be applied to meta-heuristic algorithms in the job-shop scheduling problem(JSP).Firstly,this paper delves into the importance of domain knowledge in optimization algorithm *** that,the development of different methods for the JSP are reviewed,and the domain knowledge in it for meta-heuristic algorithms is summarized and *** of this domain knowledge are analyzed,showing it is indispensable in ensuring the optimization performance of meta-heuristic ***,this paper analyzes the relationship among domain knowledge,optimization problems,and optimization algorithms,and points out the shortcomings of the existing research and puts forward research *** paper comprehensively summarizes the domain knowledge in the JSP,and discusses the relationship between the optimization problems,optimization algorithms and domain knowledge,which provides a research direction for the metaheuristic algorithm design for solving the JSP in the future.
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