Design for Optimally Routing and Scheduling a Tow Train for Just-in-Time Material Supply of Mixed-Model Assembly Lines

Beixin Xia, Mingyue Zhang, Yan Gao, Jing Yang and Yunfang Peng ()
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Beixin Xia: School of Management, Shanghai University, Shanghai 200444, China
Mingyue Zhang: School of Management, Shanghai University, Shanghai 200444, China
Yan Gao: School of Communication, East China University of Political Science and Law, Shanghai 201620, China
Jing Yang: School of Management, Shanghai University, Shanghai 200444, China
Yunfang Peng: School of Management, Shanghai University, Shanghai 200444, China

Sustainability, 2023, vol. 15, issue 19, 1-16

Abstract: With the increase in product varieties, the combination of supermarkets and tow trains is being adopted by more automobile manufacturers for part feeding, especially in mixed-flow assembly lines. This paper focuses on the routing, scheduling, and loading problems of a single towed train that transports parts from one supermarket to the workstation buffer in a mixed-flow assembly line and aims to optimize the loading of the tow train, the optimal delivery schedule and route, and the appropriate departure time to minimize shipping and line inventory costs. To enable part feeding in line with the just-in-time (JIT) principle, a new mixed-integer mathematical model from nonlinearity to linearity and a novel artificial immune genetic algorithm-based heuristic are proposed. Both methods can provide reasonable solutions compared by minimizing the route length and inventory level in terms of speed, and the genetic algorithm shows better performance on a large scale.

Keywords: mixed-model assembly line; part feeding; mixed-integer mathematical model from nonlinearity to linearity; artificial immune genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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