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Integrated returnable transport items inventory model with uncertain demand considered safety stock
|Authors: ||Chen, Lu-An|
|Contributors: ||NTOU:Department of Transportation Science|
Returnable transport items;Integrated inventory model;Safety stocks;Exponential distribution;Uncertain environment
|Issue Date: ||2020-07-02T08:25:55Z
|Abstract: ||過去多年來，公司企業的競爭有愈趨激烈的現象，在如此高度競爭的環境下，許多研究者也投入更多的關注在資源浪費的減少以及整合供應鏈的管理上。近年來對於公司來說，為了減少包裝材料的使用，普遍使用所謂的可回收運輸器具(貨櫃、木板箱)等可重複使用的包裝材料來運送產品到買家手中以確保處理及運送過程安全無虞，而使用完的包裝材料將會被集中起來並回收至供應商做為下一次運送使用，但由於一些不可預期的因素，像是貨櫃的損壞、客戶端的勞力短缺等等，使貨櫃的回收時間趨於隨機變化，甚至有回收延誤的可能，容易造成供應鏈的競爭力衰退。因此，本篇研究主要目的為建構一套單一供應商單一買家的整合存貨模型並考慮安全存貨量來因應可回收運輸器具沒有足夠庫存下的風險，同時可回收運輸器具回收時間被假設為隨機的並符合指數分配，此外，本研究也考慮在不確定環境下採用模糊理論來模擬買家的年需求率以獲得更加真實的結果，由於本篇文章是以Kim et al. (2014)當作基礎再加以延伸，因此模式建立的部分分別以基本模式及進階模式來做比較，並以貨櫃的運送批量及安全存貨量做為決策變數來計算一階微分及二階微分以證明其存在最佳解使總成本最小化，接著建立一套求解演算法來概述求解的過程，最後，數值案例分析將以Matlab 2019a來做計算，並藉由單因子、雙因子敏感度分析法及各項圖表來說明得到的結果以及本研究所帶來的貢獻。|
For many years, the greatly competition environment has made many researchers pay much attention to the reduction of resource consumption and management activities of integrated supply chain. Generally, so-called returnable transport items (RTIs) are used to deliver finished products in order to facilitate handling or safe transportation to the customer for companies in recent years. Empty RTIs are collected at the retailer and returned to the supplier for the next shipment. Because of some unpredictable factors, such as damages of RTIs that need to be performed by retailers, labor shortage to the customer, the RTIs return lead time is considered to be stochastic in this paper and delays may even occur which can cause the competitiveness of supply chain decline. Thus, this research develops a single supplier single retailer integrated inventory model by considering safety stocks of RTIs to avoid the risk of stockouts and RTI return time is assumed to be stochastic and compliant with exponential distribution. In addition, we also advanced this new model by fuzzifying retailer’s demand rate for finished products to acquire more realistic results under uncertain environment. Since this paper is based on Kim et al. (2014), the model is composed of the basic model and the advanced model. Moreover, the RTIs lot size and safety stock are used as decision variables to compute the first-order derivative and the second-order derivative which prove that the optimal solution exists to minimize the total cost. A set of solving procedure is established to summarize the process of solving results. Finally, the numerical example study will be calculated by using Matlab 2019a; one-way and two-way sensitivity and various charts will be presented to illustrate the results and the contributions of this paper.
|Appears in Collections:||[運輸科學系] 博碩士論文|
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