Paper Info
Title
An Adaptive Real-Time Scheduling Method for Flexible Job Shop Scheduling Problem With Combined Processing Constraint
Abstract
Flexible job shop scheduling problem with combined processing constraint is a common scheduling problem in assembly manufacturing industry. However, traditional methods for classic flexible job shop scheduling problem (FJSP) cannot be directly applied. To address this problem, the concepts of `combined processing constraint' and 'virtual operation' are studied and introduced to simplify and transform FJSP with combined processing constraint into FJSP. A Multi-agent system (MAS) for FJSP is used for fitting the requirement of building complex, flexible, robust and dynamic manufacturing scheduling. On this basis, a novel adaptive real-time scheduling method for MAS is further proposed for better adaptability and performance. This method solves the previously converted problem and conquers the shortcoming of poor performance of traditional single dispatching rule method in MAS. In this approach, the scheduling process is modeled as contextual bandit, so that each job agent can select the most suitable dispatching rules according to the environment state after learning to achieve scheduling optimization. The proposed method is compared with some common dispatching rules that have been widely used in MAS. Results illustrate the high performance of the proposed method in a simulated environment.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2938548
IEEE ACCESS
Keywords
DocType
Volume
Multi-agent system,flexible job shop scheduling problem,combined processing constraint,contextual bandit
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Haihua Zhu192.37
Ming Chen262.46
Zequn Zhang300.34
Dunbing Tang400.34