A Multiple-Buyer Single-Vendor in a Continuous Review Inventory Model with Ordering Cost Reduction Dependent on Lead Time

In this competitive environment, integration between two or more business entities is an important way to gain competitive advantages as it lowers supply chain cost. This paper presents a multiple-buyer single-vendor integrated inventory system with ordering cost reduction on lead time. The options of ordering cost reduction included lead time of every buyer can be reduced at an added crash cost. Lead time plays a vital role in supply chain management and inventory management system. A lead time means that time gap between the placing of an order and its actual arrival in the inventory. In this paper, we study a continuous review model. The model is formulated to integrated total cost of the vendor-buyers system to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries between the vendor and buyers in a production cycle. Finally, a numerical example and effects of key parameter are included to illustrate the results of the proposed model

An Integrated Single Vendor-Buyer Stochastic Inventory Model with Partial Backordering under Imperfect Production and Carbon Emissions

This paper develops an integrated single vendor single buyer inventory model with imperfect quality and environmental impact. The demand during lead time is assumed to be stochastic and follows the normal distribution. An integrated system with controllable lead time and logarithmic investment to reduce the defective percentage is discussed in this model.100% error-free screening process is adopted by the buyer to separate defective and non-defective items. We assume that shortages are allowed and are partially backordered at the buyer’s end. Logistics management is the component of supply chain management that focusses on how and when to get raw materials, intermediate products and finished goods from their respective origins to their destinations.Thus, transportation play a major role in supply chain. As transportation increases, it affects the weather by the matter of carbon emission.The fixed and variable carbon emission cost for both vendor and buyer is considered. The prime motive is to determine the optimal policies regarding optimal order quantity, reorder point, lead time and the number of lots delivered in a production run by minimizing the expected total cost of the system. Finally, a numerical example is provided to demonstrate the model

Optimal consignment stocking policies for a supply chain under different system constraints

The research aims are to enable the decision maker of an integrated vendor-buyer system under Consignment Stock (CS) policy to make the optimal/sub-optimal production/replenishment decisions when some general and realistic critical factors are considered. In the system, the vendor produces one product at a finite rate and ships the outputs by a number of equal-sized lots within a production cycle. Under a long-term CS agreement, the vendor maintains a certain inventory level at the buyer’s warehouse, and the buyer compensates the vendor only for the consumed products. The holding cost consists of a storage component and a financial component. Moreover, both of the cases that the unit holding costs may be higher at the buyer or at the vendor are considered. Based upon such a system, four sets of inventory models are developed each of which considers one more factor than the former. The first set of models allows a controllable lead-time with an additional investment and jointly determines the shipping size, the number of shipments, and the lead time, that minimize the yearly joint total expected cost (JTEC) of the system. The second set of models considers a buyer’s capacity limitation which causes some shipments to be delayed so that the arrival of these shipments does not cause the buyer’s inventory to go beyond its limitation. As a result, the number of delayed shipments is added as the fourth decision variable. A variable demand rate is allowed in the third set of models. Uncertainty caused by the varying demand are controlled by a safety factor, which becomes the fifth decision variable. Finally, the risk of obsolescence of the product is considered in the fourth model. The first model is solved analytically, whereas the rest are not, mainly because of the complexity of the problem and the number of variables being considered. Three doubly-hybrid meta-heuristic algorithms that combine two different hybrid meta-heuristic algorithms are developed to provide a solution procedure for the rest of models. Numerical experiments illustrate the solution procedures and reveal the effects of the buyer’s capacity limitation, the effects of the variable demand rate, and the effects of the risk of obsolescence, on the system. Furthermore, sensitivity analysis shows that some of the system parameters (such as the backorder penalty, the extra space penalty, the ratio of the unit holding cost of the vendor over that of the buyer) are very influential to the joint system total cost and the optimal solutions of the decision variables

[[alternative]]The Impact of Quality and Lead Time on the Supply Chain Model

計畫編號：NSC93-2416-H032-002研究期間：200408~200507研究經費：333,000[[abstract]]由於電腦網路技術的進步及實體運輸系統的發達，「供應鏈管理」近年來逐漸發展 成一重要的領域。供應鏈管理的基本原則是利用有效率的方法，整合價值鏈上的買賣雙 方，賣方能夠在適當的時間，生產適當數量的高品質商品，並在適當的期間內送達買方 手上，使得整體系統成本最小化。基於這個理念，供應鏈的上下游廠商之間必需要建立 策略聯盟關係，利用一些有效率的方法，提升商品、服務及資訊分享的水準，才能真正 發揮供應鏈營運的績效。 再者，長久以來，存貨模式大都是基於買方或賣方單方面的考量，來探討生產及訂 購策略等問題，如此往往使雙方資訊無法整合而造成損失。近年來，及時化的製造策略 受到廣泛利用，由於其專注於買方與賣方的整合，因此需要買方與賣方能夠充分合作， 方可利用雙方資訊的整合，訂定合理的長期採購合約，做到真正的及時化採購，從而降 低相關存貨系統的總成本。 本計劃是一為期二年的個別型計劃。本計劃之第一年主要是考慮當需求不確定，且 前置時間的長度可控制及買方收到的批量中含有不良品的情況下，如何整合買方和賣方 的製造與訂購策略，並提出兩個整合存貨模型。在本研究中，首先我們採全部檢查(full-lot inspection)的策略來檢查批量中的不良品項。針對此檢查策略，我們假設前置時間內的 需求量服從常態分配，其次探討前置時間內需求量的機率分配為未知的情形，並且利用 大中取小分配不拘程序求解。我們亦分別針對此兩種情形(前置時間內需求量的機率分 配為常態分配或分配不拘)建立求得最適生產、訂購策略之演算法，並利用數值範例說 明買賣雙方整合後的利益，確實是高於整合前的個別利益。同時，本研究也將分析各參 數變動對於決策所造成的影響，作為提供給管理者之重要參考依據。 第二年：我們進一步考慮利用部份檢查(sub-lot inspection)策略於買賣雙方之整合存 貨模式。此外，我們亦探討數量折扣(quantity discount)在供應鏈模式中之影響。如同第 一年計劃，假設前置時間內的需求量服從常態分配及機率分配為未知的情況。並分別對 存貨數學模型找出最佳解。針對上述的存貨模型，分別就聯合決策、買方主導與賣方主 導等三種情況推導買、賣方之最適批量;並探討在何種情況下的存貨總成本為最小。最 後，以數值範例來說明其使用之方法，並顯示其所能帶來的經濟效益。[[sponsorship]]行政院國家科學委員

[[alternative]]The Study of Two-Echelon Supply Chain Inventory Model with Defective Items and Controllable Lead Time

計畫編號：NSC94-2416-H032-002研究期間：200508~200607研究經費：359,000[[abstract]]傳統的存貨模式大都是基於買方或賣方單方面的考量，來探討生產及訂購策略等問 題，如此往往使雙方資訊無法整合而造成損失。近年來，及時化的製造策略受到廣泛 利用，由於其專注於買方與賣方的整合，因此需要買方與賣方能夠充分合作，方可利 用雙方資訊的整合，訂定合理的長期採購合約，做到真正的及時化採購，從而降低相 關存貨系統的總成本。 近年來，有關整合性的存貨模式愈來愈受到重視。過去的相關研究大多著重於買賣 雙方最適訂購、生產與運送批量的決定，並未考慮到當批量中含有不良品時對整合買 賣雙方總成本的影響。在實務上，因為生產製造過程的瑕疵，管理維護不當，或是運 送過程的不小心，買方經常會在訂購批量中發現不良品。 本計劃主要是考慮當需求不確定，且前置時間的長度可控制及買方收到的批量中含 有不良品的情況下，如何整合買方和賣方的製造與訂購策略，並提出兩個整合存貨模 型。在本研究中，我們採部份檢查(sub-lot inspection)的策略來檢查批量中的不良品項。 針對此檢查策略，我們假設前置時間內的需求量服從常態分配，其次探討前置時間內需 求量的機率分配為未知的情形，並且利用大中取小分配不拘程序求解。我們亦分別針對 此兩種情形(前置時間內需求量的機率分配為常態分配或分配不拘)建立求得最適生 產、訂購策略之演算法，並利用數值範例說明買賣雙方整合後的利益，確實是高於整合 前的個別利益。同時，本研究也將分析各參數變動對於決策所造成的影響，作為提供給 管理者之重要參考依據。[[sponsorship]]行政院國家科學委員

Optimising replenishment policy in an integrated supply chain with controllable lead time and backorders-lost sales mixture

This paper aims to optimize the inventory replenishment policy in an integrated supply chain consisting of a single supplier and a single buyer. The system under consideration has the features such as backorders-lost sales mixture, controllable lead time, stochastic demand, and stockout costs. The underlying problem has not been studied in the literature. We present a novel approach to formulate the optimization problem, which is able to satisfy the constraint on the number of admissible stockouts per time unit. To solve the optimization problem, we propose two algorithms: an exact algorithm and a heuristic algorithm. These two algorithms are developed based on some analytical properties that we established by analysing the cost function in relation to the decision variables. The heuristic algorithm employs an approximation technique based on an ad-hoc Taylor series expansion. Extensive numerical experiments are provided to demonstrate the effectiveness of the proposed algorithms