廉莲

个人信息Personal Information

副教授

硕士生导师

性别:女

毕业院校:法国里尔中央理工大学

学位:博士

所在单位:交通运输系

学科:交通运输规划与管理

办公地点:大连理工大学土木实验4号楼516房间

电子邮箱:lian.lian@dlut.edu.cn

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Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

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论文类型:期刊论文

发表时间:2014-01-01

发表刊物:Journal of Industrial Engineering and Management

收录刊物:EI

卷号:7

期号:2 SPEC. ISSUE

页面范围:518-531

ISSN号:20138423

摘要:Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP), to discuss the method to deal with uncertainty in a manufacturing system. Design/methodology/approach: In this paper, condition based maintenance (CBM), a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA) used in the previous article (Neale & Cameron, 1979), an inserting algorithm (IA) is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme. Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM) is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed. Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA) is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.