Abstract
在訂購量與前置時間為決策變數之前提下,本文提出一個考慮數量折扣與允許部分欠撥之單一商品與多個供應商存貨模型;另外,為了使模型更臻完善,本文放寬以往的假設,使得趕工成本函數不僅受到訂購量的影響也同時受到壓縮前置時間的影響。接著,本文利用作業研究中的整數規劃方法來簡化傳統計量方法的求解程式,再運用逐步線性化方法處理非線性的問題以求解出近似全域最佳解,使得新模型不但能改善傳統計量方法僅能求得區域解的問題,還能運用一般商用運算軟體簡單求解,並且決策者可依照真實世界情況適時的加入限制式,以符合實際之需求。最後,透過範例加以驗證所提模型之正確性與實用性。
Based on both the ordered quantity and lead time as decision variable, this article proposes a single item multi-supplier model that considers inventory problems with quantity discount and backorder. To complete our model, this paper regards crash cost as a function of both the order quantity and the shortened lead time, not as a function of the shortened lead time. In this article, the integral optimization approach is used to simplify the complex multiple-step process of the traditional quantitative methods. In addition, exerting piecewise linearization techniques solves non-linear problems to find an approximate global optimization. As a result, the proposed model not only can overcome the shortcoming of the traditional quantitative methods that can merely obtain the local optimal solutions, but can be easily implemented by the common commercial programs. In addition, the resource constraints can be easily added by decision-maker to suit real-world situations. Finally, several examples are included to demonstrate the usefulness and correctness of the proposed method.
Based on both the ordered quantity and lead time as decision variable, this article proposes a single item multi-supplier model that considers inventory problems with quantity discount and backorder. To complete our model, this paper regards crash cost as a function of both the order quantity and the shortened lead time, not as a function of the shortened lead time. In this article, the integral optimization approach is used to simplify the complex multiple-step process of the traditional quantitative methods. In addition, exerting piecewise linearization techniques solves non-linear problems to find an approximate global optimization. As a result, the proposed model not only can overcome the shortcoming of the traditional quantitative methods that can merely obtain the local optimal solutions, but can be easily implemented by the common commercial programs. In addition, the resource constraints can be easily added by decision-maker to suit real-world situations. Finally, several examples are included to demonstrate the usefulness and correctness of the proposed method.
Original language | Chinese (Traditional) |
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Pages (from-to) | 229-258 |
Journal | 臺大管理論叢 |
Volume | 18 |
Issue number | 2 |
State | Published - 2008 |