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| 研究生： |
鄭弘杰 Hung-chieh Cheng |
|---|---|
| 論文名稱： |
蔬菜加工之供應鏈排程 Supply Chain Scheduling of Vegetable Process |
| 指導教授： |
廖慶榮
Ching-Jong Liao |
| 口試委員: |
王孔政
Kung-Jeng Wang 鄭元杰 Yuan-Jye Tseng |
| 學位類別： |
碩士 Master |
| 系所名稱： |
管理學院 - 工業管理系 Department of Industrial Management |
| 論文出版年： | 2009 |
| 畢業學年度： | 97 |
| 語文別： | 英文 |
| 論文頁數： | 30 |
| 中文關鍵詞： | 排程 、車輛途程問題 、塔布搜尋法 、蔬菜加工 |
| 外文關鍵詞： | Scheduling, Vehicle routing problem, Tabu search, Vegetable process |
| 相關次數： | 點閱：223 下載：3 |
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生產排程與物流配送為供應鏈中兩個重要的階段作業。目前已有相當多的文獻分別探討此兩階段之最佳化問題。在本論文中，我們以一個蔬菜加工公司為例，考慮將此兩階段結合成為單一系統，並使用生產排程模式及車輛途程問題來探討其整體之最小成本。由於車輛途程問題已被證明為NP-hard的問題，其求解時間會隨著訂單數的大小而呈指數增加，因此很難在合理的時間內找出整合此兩階段之最佳解。所以對於這個問題我們提出一個塔布搜尋法來找尋一個較佳可行解。啟發式演算法是一種快速且實用的尋優求解方法，其中塔布演算法（tabu search algorithm，TS）較能符合各種不同型態的最佳化問題。有鑑於此，本研究運用塔布演算法以有效地找出整合生產排程與物流配送兩階段總成本最小化的最適解。經由電腦運算結果指出，我們所提出的塔布搜尋法較現有的方法達到更好的成果，結果也顯示本研究所提出之方法非常適合求解此兩階段最佳化之問題。
Scheduling and vehicle routing in supply chain are two important operations. In the thesis, we consider to integrate the two parts to a single system as a vegetable processing company and minimizing total cost in machine and deliveries scheduling. The objective of the problem is to determine the number of outsource vehicles and a set of vehicle and machine schedules with minimum sum of processing cost and outsource transportation fee. The vehicle route problem is known to be NP-hard. Therefore, it is unlikely to find an optimal solution within reasonable to this problem. Meta heuristics are then considered to find the near-optimal solution in this study. We propose a tabu search (TS) algorithm to obtain a good feasible solution for the problem. Extensive computational results show that the proposed TS algorithm achieves better performance than the original and initial method.
[1] Levin, A., Penn, M., 2008. Approximation algorithm for minimizing total latency in machine scheduling with deliveries, Discrete Optimization, 5, 97-107.
[2] Ben-Daya, M., Al-Fawzan, M., 1998. A tabu search approach for the flow shop scheduling problem. European Journal of Operational Research, 109, 88-95.
[3] Li, C.L., Vairaktarakis, G., Lee, C.Y., 2004. Machine scheduling with deliveries to multiple customer locations, European Journal of Operational Research, 164, 39-51.
[4] Potts, C.N., 1980.Analysis of a heuristic for one machine sequencing with release dates and delivery times, Operations Research, 28, 1436-1441.
[5] Cordeau, J.F., Gendreau, M., Laporte, G., Potvin, J.Y., Semet, F., 2002. A guide to vehicle routing heuristics, Journal of the Operational Research Society, 53, 512-522.
[6] Glover, F., 1986. Future paths for integer programming and link to artificial intelligence. Computers and Operations Research, 13, 533-549.
[7] Hall, L.A., Shmoys, D.B., 1992. Jackson’s rule of single machine scheduling: Making a good heuristic better, Mathematics of Operations Research, 17, 22-35.
[8] Langston, M.A., 1987. Interstage transportation planning in the deterministic flow-shop environment. Operations Research, 35, 556-564.
[9] Maggu, P.L., Das, G., 1980. On 2 n sequencing problem with transportation times of jobs, Pure and Applied Mathematika Sciences, 12, 1-6.
[10] Tan, K. C., Lee, L. H., Zhu, Q. L., Ou, K., 2000. Heuristic methods for vehicle routing problem with time windows. Artificial Intelligence in Engineering, 15, 281-295.
[11] Sahni, S., Vairaktarakis, G., 1996. The master–slave paradigm in parallel computer and industrial settings. Journal of Global Optimization, 9, 357-377.
[12] Stern, H.I., Vitner, G., 1990. Scheduling parts in a combined production–transportation work cell. Journal of the Operational Research Society, 41, 625-632.
