Journal
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
Volume 72, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2021.102198
Keywords
Finite transportation condition; Flexible job shop scheduling; Digital Twin; Genetic algorithm; Transportation time
Funding
- National Natural Science Foundation of China [51805012, 51975019]
- Beijing University of Technology
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This study addresses the impact of finite transportation conditions on scheduling in the flexible job shop scheduling problem and proposes a method to improve the scheduling results. The results show that finite transportation conditions significantly affect scheduling under different scales of scheduling problems and transportation times.
Flexible job shop scheduling is one of the most effective methods for solving multiple varieties and small batch production problems in discrete manufacturing enterprises. However, limitations of actual transportation conditions in the flexible job shop scheduling problem (FJSP) are neglected, which limits its application in actual production. In this paper, the constraint influence imposed by finite transportation conditions in the FJSP is addressed. The coupling relationship between transportation and processing stages is analyzed, and a finite transportation conditions model is established. Then, a three-layer encoding with redundancy and decoding with correction is designed to improve the genetic algorithm and solve the FJSP model. Furthermore, an entityJavaScript Object Notation (JSON) method is proposed for transmission between scheduling services and Digital Twin (DT) virtual equipment to apply the scheduling results to the DT system. The results confirm that the proposed finite transportation conditions have a significant impact on scheduling under different scales of scheduling problems and transportation times.
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