| 研究生: |
林育萱 Lin, Yu-Hsuan |
|---|---|
| 論文名稱: |
考量模糊目標優先順序之整體生產規劃模式 A fuzzy goal programming for aggregate production planning model with imprecise preemptive priority |
| 指導教授: |
陳梁軒
Chen, Liang-Hsuan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
| 論文出版年: | 2008 |
| 畢業學年度: | 96 |
| 語文別: | 中文 |
| 論文頁數: | 73 |
| 中文關鍵詞: | 模糊理論 、目標規劃 、整體生產規劃 |
| 外文關鍵詞: | Fuzzy Theory, Goal Programming, Aggregate Production Planning |
| 相關次數: | 點閱:71 下載:2 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
由於全球化市場的快速發展以及國際化的趨勢,如何有效管理生產規劃對於企業而言是相當重要的課題,其關係到企業能否在競爭市場佔有一席之地。若產銷活動彼此無法有效配合,勢必將影響企業的營運績效,導致非但無法獲利,還會造成資源的浪費,因此企業必須透過發展有效的整體生產規劃來尋求解決之道。整體生產規劃仰賴企業長程產能規劃的功能以預測未來的需求量並擬訂長程產能計劃,依據實際訂貨及存貨狀況,向短期日程及存貨管制部門發出生產或存貨計劃,例如主生產排程(Master Production Schedule, MPS)以及物料需求規劃(Material Requirements Planning, MRP)等,並且適時與資本預算部門共同擬訂邊際產能決策。因此,就企業的整體生產策略及規劃層次而言,整體規劃扮演著承上接下的關鍵樞紐假設,亦是影響企業整體績效與競爭力的重要決策活動。
實務上,整體規劃當中的參數以及決策變數,例如各種成本、價格、產能、市場需求、人力需求等,受到外部資源以及內部供需的影響,皆含有相當程度的不精確性與模糊性,而決策者通常面臨含多元模糊目標的權衡取捨問題,意即不精確的目標值。本研究主要目的在於利用模糊目標規劃方法,建構整體生產規劃的數學模式,同時考量目標之間所存在的模糊優先順序,以提供給決策者作為參考。模式當中包含最大化利潤、最小化存貨水準以及最小化人力水準變動成本三個目標,並且將產能與成本方面的限制因素納入考量。
透過案例演算與數值分析,發現本研究所提出的新模式比起現有模式而言更加具有彈性,決策者可以透過設定不同的參數值以及對於模糊關係不同的定義而獲得理想的輸出解,以符合企業需求,訂定最佳的整體生產規劃。
Given the uncertainty in the production environment, this paper discusses a goal programming approach to modeling multi-product aggregate production planning (APP) problems with fuzzy goals. The proposed model addresses the problem for an international company which has many manufacturing factories around the world, and considers the production loading plans subject to certain restrictions. The three goals in the proposed model are maximizing total profits, minimizing the inventory level and minimizing the cost of changes in the workforce level.
In goal programming, the two most widely used approaches to treating the relative importance among the goals are weighted GP and preemptive priority GP. However, both approaches may be too restrictive in the modeling of real life decision making problems. In this paper, the hierarchical levels of the goals are imprecisely defined by fuzzy relations, and an additive function is used, which takes into account both the achievement degrees of the goals and the degrees of satisfaction of the fuzzy importance relations.
一、中文部分
1.王世峰,劉明德,生產與作業管理,普林斯頓國際有限公司,台北縣,民國94年。
2.李度宏,生產與作業管理,譯自Martinich, J. S., Production and Operations Management,台灣西書出版社,台北市,民國94年。
3.陳振益,吳怡慧,吳亞穎,尤丁白,簡國樑,生產與作業管理,譯自Russell, R. S. and Taylor, B. W., Operational Management,全華科技圖書股份有限公司,台北市,民國94年。
4.陳耀茂,模糊理論,譯自井上洋,天笠美知夫,模糊理論,五南圖書出版股份有限公司,台北市,民國91年。
5.傅和彥,生產管理,譯自William, J. S., Production/Operational Management,前程企業管理有限公司,台北縣,民國91年。
6.潘俊明,生產與作業管理,三民書局股份有限公司,台北市,民國93年。
7.簡禎富,決策分析與管理-全面決策品質提升之架構與方法,雙葉書廊,台北市,民國94年。
二、英文部分
1. Akoz, O. and Petrovic, D., “A fuzzy goal programming method with imprecise goal hierarchy,” European Journal of Operational Research, 181, 1427-1433, 2007.
2. Baykasoglu, A., “MOAPPS 1.0: aggregate production planning using the multiple-objective tabu search,” International Journal of Production Research, 39, 16, 3685 - 3702, 2001.
3. Bellman, R. E. and Zadeh, L. A., “Decision-making in a fuzzy environment,” Management Science, l7, 141-164, 1970.
4. Bowman, E. H., “Production scheduling by the transportation method of linear programming,” Operations Research, 4, 100-103, 1956.
5. Bowman, E. H., “Consistency and optimality in managerial decision making,” Management Science, 9, 310-321, 1963.
6. Buffa, E. S. and Taubert, W. H., Production-Inventory System: Planning and Control, Richard D. Irwin, Inc., Illinois, 1972.
7. Byrne, M. D. and Bakir, M. A., “Production planning using a hybrid simulation-analytical approach,” International Journal of Production Economics, 59, 305-311, 1999.
8. Chang, C. T., “Binary fuzzy programming,” European Journal of Operational Research, 180, 29-37, 2007.
9. Charnes, A. and Cooper, W. W., Management Models and Industrial Applications of Linear Programming, John Wiley and Sons, New York, 1961.
10. Chen, L. H. and Tsai, F. C., “Fuzzy goal programming with different importance and priorities,” European Journal of Operational Research, 133, 548-556, 2001.
11. Delgado, M., Herrera, F., Herrera-Viedma, E. and Martinez, L., “Combining numerical and linguistic information in group decision making,” Information Science, 107, 177-194, 1998.
12. Dobois, D. and Prade, H., “Operations on fuzzy numbers,” International Journal of Systems Science, 9, 613-626, 1978.
13. Gass, S. I., “The setting of weights in linear goal-programming problem,” Computers and Operations Research, 14, 3, 227-229, 1987.
14. Ghyym, S. H., “A semi-linguistic fuzzy approach to multi-actor decision-making: application to aggregate of experts’ judgment,” Annals of Nuclear Energy, 1097-1112, 1999.
15. Hannan, E. L., “Linear programming with multiple fuzzy goals,” Fuzzy Sets and Systems, 6, 235-248, 1981.
16. Hax, A. and Meal, H. C., “Hierarchical Integration of Production Planning and Scheduling,” Studies in Management Science, Logistics, North-Holland-American Elsevier, New York, 1975.
17. Holt, C. C., Modigliani, F. and Simon, H. A., “A linear decision rule for production and employment scheduling,” Management Science, 2, 1-30, 1955.
18. Jones, C. H., “Parametric production planning,” Management Science, 13, 843-866, 1967.
19. Krajewski, L. J. and Rizman, L. P., Operational Management: Process and Value Chains, Pearson Education Inc., New Jersey, 2002.
20. Lin, C. C., “A weighted max–min model for fuzzy goal programming,” Fuzzy Sets and Systems, 407-420, 2004.
21. Masud, A. S. M. and Hwang, C. L., “An aggregate production planning model and application of three multiple objective decision methods,” International Journal of Production Research, 18, 741-752, 1980.
22. Narasimhan, R., “Goal programming in a fuzzy environment,” Decision Sciences, 11, 325-336, 1980.
23. Romero, C., “A general structure of achievement function for a goal programming model,” European Journal of Operational Research, 153, 675-686, 2004.
24. Singhal, K. and Adlakha, V., “Cost and shortage trade-offs in aggregate production planning,” Decision Sciences, 20, 158-165, 1989.
25. Stephen, C. H. L., Wu, Y. and Lai, K. K., “Multi-site aggregate production planning with multiple objectives: a goal programming approach,” Production Planning and Control, 14, 5, 425-436, 2003.
26. Steuer, R. E., Multiple Criteria Optimization: Theory, Computation, and Application, John Wiley and Sons, Singapore, 1986.
27. Tamiz, M., Jones, D. and Romero, C., “Goal programming for decision making: An overview of the current state-of-the-art,” European Journal of Operational Research, 111, 569-581, 1998.
28. Tang, J., Fung, R. Y. K. and Yung, K. L., “Fuzzy modeling and simulation for aggregate production planning,” International Journal of Systems Science, 34, 12, 661-673, 2003.
29. Tang, J., Wang, D. and Fung, R. Y. K., “Fuzzy formulation for multi-product aggregate production planning,” Production Planning and Control, 11, 7, 670-676, 2000.
30. Taubert, W. H., “A search decision rule for the aggregate scheduling problem,” Management Science, l4, 343-359, 1968.
31. Tiwari, R. N., Dharmar, S. and Rao J. R., “Fuzzy goal programming- An additive model,” Fuzzy Sets and Systems, 24, 27-34, 1987.
32. Wang, R. C. and Liang, T. F., “Application of fuzzy multi-objective linear programming to aggregate production planning,” Computers and Industrial engineering, 46, 17-41, 2004.
33. Xia, H. C., Li, D. F., Zhou, Y. J. and Wang, J. M., “Fuzzy LINMAP method for multiattribute decision making under fuzzy environments,” Journal of Computer and System Science, 72, 741-759, 2006.
34. Zadeh, L. A., “Fuzzy Sets,” Information and Control, 8, 338-353, 1965.
35. Zimmermann, H. J., “Fuzzy programming and linear programming with several objective function,” Fuzzy Sets and Systems, 1, 45-56, 1978.