臺灣博碩士論文加值系統

封閉式供應鏈網路設計為結合正向物流與逆向物流的廠址選擇問題。因應社會上的環境波動與商場上之競爭激烈，回收產品重新製造販售送至顧客，以達到綠色環保及減少成本等優勢。當決策者設計此供應鏈網路時，常須面對不確定之因素，如：顧客需求數量、產品回收數量、運送成本…等不確定性參數。若不確定性參數無法準確的控制與預測，則可能造成錯誤決策，進而影響成本及營運狀況。因此，如何有效控制與準確預測不確定性參數為當今企業之重要課題。
對於封閉式供應鏈網路不確定性參數之廠址選擇模型，本研究使用兩階段互動式可能性規劃尋找首選妥協解，並與目前幾種模糊規劃方法進行比較與分析。經過實驗測試與分析，本研究所使用TH之模糊方法較其他模糊規劃方法有效率且快速取得平衡妥協解。

Closed-loop supply chain network design is a facility location problem combined with forward and reverse logistics. In order to reflect the environmental fluctuations and the market competitiveness, recycled products will be re-manufactured and sold to obtain the advantages of achieving the green environmental protection and reducing the cost. Decision makers need to consider the uncertain factors, such as the quantity of customer demand, the quantity of product recovery, the transportation cost and the others, to design the supply chain network. It may cause wrong decisions and affect the operating cost conditions if uncertain parameters cannot be accurately predicted and controlled. Therefore, how to control and predict the uncertain parameters is an important issue in nowadays business environment.
For the facility location model in a closed-loop supply chain network under uncertainty, this study uses a two-stage interactive possibilistic programming approach to obtain a preferred compromise solution and compare with current common fuzzy approaches. After computing experimental testing, we can find that this study based on TH fuzzy approach obtains more efficient balanced compromise solution than other fuzzy approaches.

誌謝 I
摘要 II
Abstract III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1研究背景 1
1.2研究動機 2
1.3研究目的 4
1.4研究流程 4
第二章 文獻探討 7
2.1逆向物流與封閉式供應鏈網路 7
2.2逆向物流與封閉式供應鏈網路相關模型 11
2.2.1確定性模型 11
2.2.2不確定性模型 14
2.3模糊數學規劃 22
2.3.1模糊集合理論 24
2.3.2兩階段互動式可能性規劃方法 26
第三章 建構數學模型 33
3.1問題敘述 33
3.2確定性參數之網路模型 34
3.3不確定性參數之網路模型 37
第四章 模型分析 43
4.1參數設定 43
4.2分析架構 45
4.3分析結果 46
4.3.1參數分析 47
4.3.2模糊方法之比較與分析 52
第五章 結論與未來展望 67
參考文獻 69
附錄一 三組Data 參數表 73
附錄二 悲觀值與樂觀值測試結果 77
附錄三 最小接受能度等級β測試結果 79
附錄四 TH方法與SO方法之γ值測試結果 81
附錄五 模糊方法測試結果 85
附錄六 LINGO 11.0程式碼 89
附錄七 參數產生程式 91

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