應用Fuzzy c-Means演算法之物流中心位址決策模式研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：24

、訪客IP：18.189.171.188

姓名

鍾武勳(Wu-Hsun Chung) 查詢紙本館藏

畢業系所

工業管理研究所在職專班

論文名稱

應用Fuzzy c-Means演算法之物流中心位址決策模式研究
(A Fuzzy c-Means Based Model for Determining the Locations of Distribution Centers)

相關論文

★ 佈置變更專案工程的執行研究－以H公司研發單位為例	★ MIL-STD-1916、MIL-STD-105E與結合製程能力指標之抽樣檢驗計畫
★ 建構客戶導向的製造品質資訊系統--以某筆記型電腦專業代工廠商為例	★ GMP藥廠設施佈置規劃的探討--以E公司為研究對象
★ 品質資訊系統之規劃與建構 -- 以某光碟製造公司為研究對象	★ 從製程特性的觀點探討生產過程中SPC管制圖監控運用的適切性 -- 以Wafer Level 封裝公司為例
★ 六標準差之應用個案研究-以光學薄膜包裝流程改善為例	★ 利用六標準差管理提昇中小企業之製程品質-以錦絲線添加防銹蠟改善為例
★ 專業半導體測試廠MES 系統導入狀況、成果及問題之探討-以A 公司為例	★ 以RFID技術為基礎進行安全管理導入－以A公司為例
★ 如何提昇產品品質及降低成本—以光碟壓片廠A公司為例	★ ERP導入專案個案分析—以半導體封裝廠A公司為例
★ 石英元件製造業之延遲策略應用— 以T公司為研究對象	★ 十二吋晶圓廠自動化搬運系統規劃與導入—以A公司為例
★ 半導體封裝產業之生產革新改善活動-A半導體股份有限公司導入經驗探討-	★ 外包商評選模式之研究－以TFT LCD中小尺寸面板產業為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

在現今全球化的世界經濟活動中，供應鍊管理一直是一個極重要的議題。而在供應鍊當中，物流中心（Distribution Center）更扮演了重要角色。其中物流中心的位址對運作成本有極大的影響。本論文即是提出一應用「Fuzzy c-Means 演算法」之物流中心位址決策模式，用以解決多設施位址之決策問題。此決策模式首先採用Fuzzy c-Means 群聚演算法（Fuzzy c-Means），將所有地理上相近之需求點加以分群，形成數個預先決定數量之群集（Cluster）。而在每一個群集中，僅有一個物流中心供應其群集中之需求點。接著採用「重心法」（The Exact Center of Gravity）求取每一個群集所在區域成本最低之最佳位址（Optimal Location）。若「重心法」求取之最佳位址（Optimal Location）因種種環境限制下不可行，則使用模擬退火法（Simulated Annealing）加以修正改善，以求取新的最佳位址。

摘要(英)

Supply chain management is a critical issue in the integrated world economy. Further, distribution center plays a key role in supply chain as the location of distribution centers has a significant impact on the operation cost. In this thesis, a Fuzzy c-Means based model to deal with the multi-facility problem is proposed. First, a clustering algorithm, Fuzzy c-Means, is used to classify demand points with highly similar geographic features to obtain several clusters in a predetermined number. Each cluster has a distribution center supplying all its demand points. Next, the exact center of gravity approach is applied to optimize the location of the distribution center with the minimum cost in each cluster. Finally, if the location obtained from the exact center-of-gravity approach is not infeasible (in the areas which cannot satisfy the basic requirements of a distribution center), a heuristics optimization technique, simulated annealing (SA), is used to improve the optimal solution.

關鍵字(中)

★ 倉庫位置
★ 位址決策
★ 模糊群集演算法
★ 倉庫
★ 物流中心
★ 群集演算法

關鍵字(英)

★ Warehouse
★ Distribution Center
★ Cluster Algorithm
★ Fuzzy c-mean
★ Location Decision
★ Warehouse Location

論文目次

Abstract Ⅰ
Table of Content Ⅲ
List of Figures Ⅴ
List of Tables Ⅵ
Chapter I Introduction ...1
1.1 Background and Motivation 1
1.2 Thesis Objectives 2
1.3 Thesis Scope 2
1.4 Thesis Structure 3
Chapter II Literature Review ...5
2.1 Definitions and Development of Distribution Centers 5
2.1.1 Definitions and Characteristics of a Distribution Center .. 6
2.1.2 Objectives and Categories of a Distribution Center . ..7
2.2 Location Problems of Warehouses 7
2.2.1 Introduction of a Location Problem ...7
2.2.2 Applications of Location Theory ...7
2.2.3 Solution Approaches for Location Problems .10
Chapter III Methods .13
3.1 Collect the Feature Data of all Demand Points 15
3.2 Decide the Number of Distribution Centers 15
3.3 Apply Fuzzy c-Means to Cluster the Demand Points... 15
3.4 Use the Exact Center-of-Gravity Approach to Find the Optimal Location 18
3.5 Use Simulated Annealing to Search the Optimal Location in Feasible Areas of Each Cluster 24
Chapter IV An Example .27
4.1 Example Description 27
4.1.1 Example Background .27
4.1.2 Example Objective 27
4.2 Problem Solving Process 28
4.2.1 Collect the Feature Data of all Demand Points .28
4.2.2 Decide the Number of Distribution Centers .30
4.2.3 Apply Fuzzy c-Means to Cluster the Demand Points .27
4.2.4 The Exact Center-of-Gravity Approach to Find the Optimal Location .34
4.2.5 Simulated Annealing (SA) to Search the Optimal Location in Feasible Areas .45
4.3 Computation Result... 50
Chapter V Conclusion and Recommendation .57
5.1 Conclusion 57
5.2 Recommendation for Further Research 57
Reference .59

參考文獻

1. Armour, G. C., and Buffa, E. S., 1963, “A Heuristic Algorithm and Simulation Approach to Relative Location of Facilities,” Management Science, Vol. 9, No. 2, pp. 294-299.
2. Ballou, R. H., 2004, Business Logistics/Supply Chain Management, 5th ed., New Jersey: Pearson Prentice Hall.
3. Baxter, J., 1984, “Depot Location: A Technique for the Avoidance of Local Optima,” European Journal of Operation Research, Vol. 18, No.2, pp. 208-214.
4. Bezdek, J. C., 1981, Pattern Recognition with Fuzzy Objective Function Algorithms, New York: Plenum Press.
5. Bowersox, D. J., and Closs, D. J., 1996, Logistical Management, 1st ed., New York: McGraw-Hill.
6. Brandeau, M. L., and Chiu, S. S., 1989, “An Overview of Representative Problems in Location Research,” Management Science, Vol. 35, No. 6, pp. 645-674.
7. Cavinato, J. L., 1989, Transportation-Logistics Dictionary, 3rd, ed., Washington: International Thomson Transport Press.
8. Chiu, S. S., Berman, O., and Larson, R. C., 1985, “Locating a Mobile Server Queuing Facility on a Tree Network,” Management Science, Vol. 31, No. 6, pp. 764-772.
9. Cornuejols, G., and Fisher, M. L., 1977, “Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms,” Management Science, Vol. 23, No. 8, pp. 789-810.
10. Dasarathy, B. and White, L. J., 1980, “A Maxmin Location Problem,” Operation Research, Vol. 28, No. 6, pp. 1385-1401.
11. Dearing, P. M., Francis, R. L., and Lowe, T. J., 1976, “Convex Location Problems on Tree Networks,” Operations Research, Vol. 24, No.4, pp. 628-642.
12. Dokmeci, V. F., 1977, “A Quantity Model to Plan Regional Health Facility Systems,” Management Science, Vol. 24, No. 4, pp. 411-419.
13. Drucker, P. F., 1969, “Physical Distribution: The Frontier of Modern Management,” in Bowersox, D. J., Bernard, J. L., and Edward, S. (eds.), Readings in Physical Distribution Management, New York: Macmillan.
14. El-Shaieb, A. M., 1973, “A New Algorithm for Locating Sources among Destinations,” Management Science, Vol. 31, No. 6, pp. 221-231.
15. Garfinkel, R. S., Neebe, A. W., Rao, M. R., 1977, “The m-Center Problem: Minimax Facility Location,” Management Science, Vol. 23, No. 10, pp. 1133-1142.
16. Hakimi, S. L., 1983, “On Locating New Facilities in a Competitive Environment,” European Journal of Operation Research, Vol. 12, No.1, pp. 29-35.
17. Hillier, F. S., and Connors, M. M., 1966, “Quadratic Assignment Problem Algorithms and the Location of Invisible Facilities,” Management Science, Vol. 13, No. 1, pp. 42-57.
18. Jaccard, P., 1908, “Nouvelles researches sur la distribution florale,” Bull Soc Vaud Sci Nat, Vol. 44, pp. 223-292.
19. Kuehn, A. A. and Hamburger, M. J., 1963, “A Heuristic Program for Locating Warehouses,” Management Science, Vol. 9, No. 14, pp. 643-666.
20. LaLonde, B. J. and Zinszer, P. H., 1976, Customer Service: Meaning and Management, Chicago: National Council of Physical Distribution Management.
21. Lundqvist, L., and Mattsson, L. G., 1983, “Transportation Systems and Residential Location,” European Journal of Operation Research, Vol. 12, No.3, pp. 279-294.
22. Mansfield, E., and Wein, H. H., 1958, “A Model for the Location of a Railroad Classification Yard,” Management Science, Vol. 4, No. 3, pp. 292-313.
23. Nambiar, J. M., Gelders, L. F., and Van Wassenhove, L. N., 1981, “A Large-Scale Location-Allocation Problem in the Natural Rubber Industry,” European Journal of Operation Research, Vol. 6, No.2, pp. 183-189.
24. Price, W. L. and Turcotte, M., 1986, “Locating a Blood Bank,” Interfaces, Vol. 16, No. 5, pp. 17-26.
25. Romesburg, H. C., 1984, Cluster Analysis for Researchers, Belmont CA: Wadsworth.
26. Ross, T. J., 1995, Fuzzy Logic with Engineering Applications, New York: McGraw-Hill.
27. Stevenson, W. J., 2002, Operations Management, 7th ed., New York: McGraw-Hill.
28. Weber, A., 1909, Uber den Standort der Industrien; 1929, translated as Alfred Webers’ Theory of the Location of Industries, University of Chicago.
29. Wesolowsky, G. O. and Love, R. F., 1972, “A Nonlinear Approximation Method for Solving a Generalized Rectangular Distance Webber Problem,” Management Science, Vol. 18, No. 11, pp. 656-663.
30. Wilson, R. and Delaney, R. V., 2000, “11th Annual State of Logistics Report,” Cass Information Systems and ProLogis, Washington, DC: National Press Club.

指導教授

何應欽(Ying-Chin Ho)

審核日期

2006-1-20

推文