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  • 學位論文

在供應商管理存貨系統下探討模組化產品與運輸問題以減少碳足跡使利潤最大化

Considering modular product and transportaion to reduce carbon footprint for maximizing profit under Vendor Managed Inventory system

指導教授 : 邱裕方
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摘要


隨著世界各國對於環保意識逐漸的提升,綠色的概念不僅止於回收或是再製造的部份,而是更廣義的產品可再利用性或是替代性的考量以及有關生產或運輸所產生碳排放的控制。所以本研究將以可減少長鞭效應且具有協調功能的供應商管理存貨 (Vendor Managed Inventory, VMI)供應鏈系統,作為本研究的主要架構,以減少因長鞭效應而產生商品的浪費。但儘管有相當多的庫存控制和運輸管理研究,但卻少有文獻將此兩問題結合去探討,而考慮運輸問題更能確實訂定最佳之訂購量或庫存水準。除此之外,本研究選擇綠色概念中,擁有較高再利用性以及可替代性的模組化產品作為探討的產品品項,並且同時考量在運輸途中所會產生的碳足跡,以課稅的方式加入成本模式中予以探討。本研究將透過KKT法找出最適的銷售數量以及最適的產品模組化程度,使整體供應鏈之利潤最大化。並且由數值範例中,針對不同的參數與整體供應鏈的利潤進行敏感度分析,以了解參數對於整體利潤的影響程度。最後,再利用基因演算法找出近似解,與KKT法比較在求解本問題時,是否存在著顯著性的差異。

並列摘要


Due to the rise of environmental consciousness, the concept of green is not just limited to the implement of recovery or remanufacturing but the considerations for reusability and substitutability of products and the control on the emission of carbon during manufacturing and transportation. This research was based on the structure of Vendor Managed Inventory (VMI) with the function of reducing bullwhip effect and coordination to avoid the waste during manufacturing. In addition, this research also focused on the modular products with the characteristics of high reusability and substitutability, furthermore, considering the occurrence of carbon footprint during transportation, by adding the tax cost function to the model. This research found the optimal sales amount and optimal modularity to maximize the profit of supply chain, then performing sensitivity analysis for each parameter and the profit of supply chain. Genetic algorithm (GA) was employed to solve the approximate solution, and to compare whether there is a significant difference between KKT method and GA for solving this problem.

參考文獻


1. Achabal, D., Mclntyre, S., Smith, S.S., Kalyanam, K (2000), A decision support system for vendor managed inventory. Journal of Retailing, 76 (4), 430–454.
2. Angulo, A., Nachtmann, H., Waller, M (2004), Supply chain information sharing in a vendor managed inventory partnership. Journal of Business Logistics, 25(1), 101–116.
3. Balan, S., Vrat, P. and Kumar, P (2009), Information distortion in a supply chain and its mitigation using soft computing approach. Omega, 37(2), 282-299.
4. Balan, S., Vrat, P., Kumar, P (2009), Information distortion in a supply chain and its mitigation by using Soft Computing Approach. OMEGA, 37 (2), 282–299.
5. Boyd, D.E., Spekman, R.E., Kamauff, J.W., Werhane, P (2007), Corporate social responsibility in global supply chains: a procedural justice perspective. Long Range Planning, 40 (3), 341–356.

被引用紀錄


趙彥婷(2012)。大學以上學歷之民眾對於碳足跡認知之研究〔碩士論文,國立屏東科技大學〕。華藝線上圖書館。https://doi.org/10.6346/NPUST.2012.00119

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