Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization. (January 2023)

• Record Type: Journal Article
• Authors: Lu, Shan; Chen, Chen; Wang, Yue; Li, Zhe; Li, Xinchao
• Is Part Of: Advanced engineering informatics. Volume 55(2023)
• Publication Date: 2023-01
• Subjects: Closed-loop manufacturing -- Mixed-integer linear programming -- Recycling process -- Manufacturing sustainability -- Iterative decomposition; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2022.101848
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.