臺灣博碩士論文加值系統

本研究在二階及三階層的供應鏈流程架構下提出一個「工廠地點設置及零售商選擇工廠問題」和一個「工廠地點設置及零售商選擇工廠與工廠選擇供料商問題」，據以探討運輸成本和產品生產成本對於供應鏈成員選擇的影響。前者「工廠地點設置及零售商選擇工廠問題」是一個包含零售商與工廠的兩階層的供應鏈設計問題。當中探討運輸成本與產品製造成本對於零售商選擇工廠以及工廠地點設置決策變數的影響。而後者「工廠地點設置及零售商選擇工廠與工廠選擇供料商問題」則是一個包含零售商、工廠、以及供料商的三階層的供應鏈設計問題。此問題同時探討上述兩類成本和原料購買成本對零售商選擇工廠、工廠選擇供料商、以及工廠地點設置決策變數的影響。本研究並針對這兩類問題發展一個「混合反覆式代理人賽局及遺傳演算的演化求解法」，並實作求解系統名為「混合代理人賽局和遺傳演算的優化系統」。此法使用交互凍結的演算架構結合遺傳演算和反覆式代理人賽局求解技術有效求解上述兩類問題。為比較本法的求解效能和品質，本研究同時建立單純遺傳演算法及交互凍結遺傳演算法進行比較。經由範例驗證與比較，本演化求解法對本研究提示的兩類問題的求解品質與收斂效果都比單純遺傳演算法以及交互凍結遺傳演算法好。此外也設計各種個案測試，探討不同情境下的供應鏈設計結果，提供供應鏈設計參考之用。

This paper presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first problem involves a number of location fixed retailers choosing a factory to supply their demands and a number of factories whose locations are to be determined. The goal is to minimize the sum of transportation and manufacturing costs. In the second problem, the raw material procurement cost is additively added, since a number of material suppliers are involved and each factory needs to select one supplier to provide the raw material. Economic factors are considered in the cost evaluations. Therefore, the partner selections (factory selection for retailers and material supplier selection for factories) will influence the manufacturing and procurement costs significantly. To solve these problems, a repeated agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM uses a mutual frozen mechanism to consecutively enable and disable the evolutions of agent gaming and genetic computation. Based on this proposed method, a prototype system, namely agent gaming/genetic algorithm hybrid optimization system (AGGAHOS) is developed to test several postulated numerical examples. Computation results of the AGGAHM are compared with those from methods of genetic algorithms and mutual frozen genetic algorithms. Results show that AGGAHM outperforms the methods solely using genetic algorithms. In addition, several supply chain design scenarios are established to verify the solutions against the practical applications.

摘要 i
Abstract ii
目錄 iii
圖目錄 v
表目錄 vii
中英文名詞對照表 viii
符號列表 xi
第1章 緒論 1
1.1 研究背景 1
1.2 研究目的 2
1.3 研究方法與流程 3
第2章 文獻探討 5
2.1 供應鏈設計 5
2.2 代理人為基計算經濟學 7
2.3 遺傳演算法和Evolver API 10
2.4 交互凍結遺傳演算法 13
第3章 工廠地點設置及供應鏈成員選擇問題 15
3.1 供應鏈架構下的問題描述與定義 15
3.2 工廠地點設置及供應鏈成員選擇問題 17
3.2.1 工廠地點設置及供應鏈成員選擇問題概述 17
3.2.2 工廠地點設置及零售商選擇工廠問題 17
3.2.3 工廠地點設置及零售商選擇工廠與工廠選擇供料商問題 23
3.3 混合反覆式代理人賽局及遺傳演算的演化求解法架構 29
3.4 反覆式代理人賽局作業 31
3.4.1 反覆式代理人賽局演化主要架構 31
3.4.2 以反覆式代理人賽局演化求解工廠地點設置及零售商選擇工廠問題中的零售商的工廠選擇變數 33
3.4.3 以反覆式代理人賽局演化求解工廠地點設置及零售商選擇工廠與工廠選擇供料商問題中的零售商的工廠選擇與工廠的供料商選擇變數 42
3.4.4 反覆式代理人賽局演化演算流程 48
3.5 遺傳演算作業 50
3.6 以混合反覆式代理人賽局及遺傳演算的演化求解法求解工廠地點設置及供應鏈成員選擇問題 53
第4章 AG/GAHOS系統範例測試 58
4.1 AG/GAHOS系統架構與介紹 58
4.1.1 系統架構說明 58
4.1.2 系統介面說明 59
4.1.3 文字檔案格式說明 61
4.2 演算法求解效能比較 63
4.3 個案研討 69
4.3.1 不同規模經濟下的個案探討 69
4.3.2 不同成本權重下的個案探討 71
4.3.3 不同運輸批量下的個案探討 72
4.4 參數設定探討 74
第5章 結論與未來展望 76
5.1 結論 76
5.2 未來研究建議 77
參考文獻 79

Beamon, B. M. (1998). "Supply chain design and analysis: Models and methods." International Journal of Production Economics, 55(3), 281-294.
Chopra, S., and Meindl, P. (2004). Supply chain management: Strategy, planning and operations, Prentica Hall, Upper Saddle River, NJ.
Cohen, M. A., and Moon, S. (1990). "Impact of production scale economics, manufacturing complexity, and transportation costs on supply chain facility networks." Journal of Manufacturing and Operations Management, 3, 269-292.
Eskigun, E., Uzsoy, R., Preckel, P. V., Beaujon, G., Krishnan, S., and Tew, J. D. (2005). "Outbound supply chain network design with mode selection, lead times and capacitated vehicle distribution centers." European Journal of Operational Research, 165(1), 182-206.
Ishibuchi, H., Sakamoto, R., and Nakashima, T. (2001). "Evolution of unplanned coordination in a market selection game " IEEE Transactions on Evolutionary Computation, 5(5), 524-534.
Jonas, H. (1999). "Use of a genetic algorithm in the adaptation part of a case-based reasoning tool for the selection of mixing equipment," Technical University of Berlin Department of Process Dynamic and Operation, Berlin.
Luss, H. (1982). "Operations research and capacity expansion problems: A survey." Operations Research, 30(5), 907-947.
Mexixell, M. J., and Gargeya, V. B. (2005). "Global supply chain design: A literature review and critique " Transportation Research Part E-logistics and Transportation Review, 41(6), 531-550.
Ong, N.-S., and Tan, W.-C. (2002). "Sequence placement planning for high-speed PCB assembly machine." Integrated Manufacturing Systems, 13(1), 35-46.
Tesfatsion, L. (2001a). "Guest editorial: Agent-based modeling of evolutionary economic systems." IEEE Transactions on Evolutionary Computation, 5(5), 437-441.
Tesfatsion, L. (2001b). "Introduction to the special issue on agent-based computational economics." Journal Of Economic Dynamics & Control, 25(3-4), 281-293.
Udaiyanathan, M., and Kaul, A. (2004). "Evolving game strategies to minimize power consumption in agent based multi-hop wireless networks," Pennsylvania State UniversityState College.
張朕豪，2004，以遺傳演算法求解轉塔式插件機的元件插置排序問題和料帶儲位安排問題，碩士論文，國立台灣大學工業工程學研究所，台北。
張嘉玲，2002，廠商創新與仿冒行為的演化－代理人基模型模擬與分析，碩士論文，國立政治大學經濟學系，台北。
許冠文，2005，遺傳演算法和啟發式裝箱演算法為基之單一容器裝填最佳化方法，碩士論文，國立台灣大學工業工程學研究所，台北。