Scheduling a single vehicle in the just-in-time part supply for a mixed-model assembly line |
| |
Authors: | Yun-Qing Rao Meng-Chang Wang Kun-Peng Wang Tou-Ming Wu |
| |
Affiliation: | 1. The State Key Laboratory of Digital Manufacturing Equipment and Technology, Wuhan 430074, China;2. The School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;3. Shenzhen Entry-Exit Inspection and Quarantine Bureau, Shenzhen 518045, China |
| |
Abstract: | This paper focuses on the scheduling of a single vehicle, which delivers parts from a storage centre to workstations in a mixed-model assembly line. In order to avoid part shortage and to cut down total inventory holding and travelling costs, the destination workstation, the part quantity and the departure time of each delivery have to be specified properly according to predetermined assembly sequences. In this paper, an optimisation model is established for the configuration that only one destination workstation is involved within each delivery. Four specific properties of the problem are deduced, then a backward-backtracking approach and a hybrid GASA (genetic algorithm and simulated annealing) approach are developed based on these properties. Both two approaches are applied to several groups of instances with real-world data, and results show that the GASA approach is efficient even in large instances. Furthermore, the existence of feasible solutions (EOFS) is analysed via instances with different problem settings, which are obtained by an orthodox experimental design (ODE). An analysis of variance (ANOVA) shows that the buffer capacity is the most significant factor influencing the EOFS. Besides this, both the assembly sequence length and distances to workstations also have noticeable impacts. |
| |
Keywords: | Vehicle scheduling Mixed-model assembly line Part supply Just-in-time GASA |
本文献已被 ScienceDirect 等数据库收录! |
|