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研究生： 陳文傑
Wen-jie Chen
論文名稱： 價格與需求波動下之多期存貨策略
Multiple-period inventory strategy under fluctuated purchasing price and demand
指導教授： 葉英傑
Ying-chieh Yeh
口試委員:
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理研究所
Graduate Institute of Industrial Management
畢業學年度： 97
語文別： 英文
論文頁數： 32
中文關鍵詞： 存貨策略 、隨機存貨模型 、時間序列
外文關鍵詞： Stochastic inventory model, Inventory strategy, Time series
相關次數： 點閱：12  下載：0 
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    • 在這篇研究中，我們結合價格波動於隨機存貨模型中，並且在多期的情況下，討論零售商應該選擇哪種存貨策略以獲得最大價差利潤。跟之前文獻不同的是，我們使用時間序列模型ARMA(p,q)當作我們的購買價格函數，以及使用簡單線性需求函數去建構一個多期存貨模型。
    當位於單一期間時，我們計算出下期的顧客期望需求以及下期漲價機率，並且提出幾個購買策略，經過比較之後，我們發現在大多數的情況下，依據下期漲價機率所製定的該策略有較佳的利潤，透過模擬數據，我們驗證該策略的最佳性，另外也對模型裡的參數做數值以及敏感度分析，最後給予零售商建議。

    In this study, we combine fluctuated purchasing price into stochastic inventory model and discuss the inventory strategy which retailers should select for obtaining maximum profit in multiple periods. Unlike previous stochastic inventory literatures, we use time series model ARMA(p,q) and simple linear price-demand function as our purchasing price model and demand function to construct a multiple-period inventory model.
    When we are in one single period, we calculate expected customer demand of next period and the mark-up probability of next period. Also, we propose some purchasing strategies. After comparing, we find out the strategy made referring the mark-up probability of next period has better profit in most conditions. We confirm the optimum of that strategy and do sensitive and numerical analysis about model’s parameters using simulation data. Finally, we give suggestions to retailers.

    Content 中文摘要 i Abstract ii Content iii List of figure v List of table v 1. Introduction 1 1.1 Background and motivation 1 1.2 Research objective 2 1.3 Research framework 3 2. Literature review 5 2.1 Inventory model with random purchasing price 5 2.2 Time series 6 2.3 Inventory strategy 7 3. The model 10 3.1 Model description 10 3.1.1 Purchasing price function and demand function 10 3.1.2 Inventories on hand and expected profit 11 3.2 Strategy 13 4. Numerical Analysis 16 4.1 Strategy comparison 16 4.2 Sensitive analysis 19 5. Conclusion and future research 29 5.1 Conclusion 29 5.2 Future research 30 Reference 31

    Reference
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