• 대한산업공학회지
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• 제34권4호
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• pp.425-432
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• 2008

While the Vendor-Managed Inventory(VMI) is a convenient inventory replenishment policy for the customer company, the supplier usually bears the burden of higher inventory and urgent shipments to avoid shortage. Recently some manufacturers begin to fix the production schedule for the next few days (such as three days). Utilizing that information can improve the efficiency of the VMI. In this study, we present a myopic optimization model using a mixed inter programming; and a heuristics algorithm. We compare the performance of the two proposed methods with the existing (s, S) reorder policy. We consider the total cost as the sum of transportation cost and inventory cost at the customer's site. Numerical tests indicate that the two proposed methods significantly reduce the total cost over the (s, S) policy.

• 대한산업공학회지
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• 제30권3호
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• pp.197-204
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• 2004

This paper deals with a supply chain with a company and its contractor that produces products by the OEM contract with the company. The supply chain of interest has two distinct features. First, the company is the supplier of raw material required in the production at the contractor. Second, the company and its contractor make a delivery shipment arrangement that the replenishment lead time is determined depending on demand process. We show that the optimal inventory policy is monotonically changed as either the replenishment setup cost or inventory holding cost becomes increased or decreased. We also present asymptotic properties of the optimal inventory policy when either the number of outstanding customer orders or the inventory level becomes very large.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.10-26
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• 2005

In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase constraint. And also, if we order at a certain date which was set by administrative convenience, we have amount constraint to order the consolidated order demands (capacity constraint). We showed this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invented a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.

• Management Science and Financial Engineering
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• 제17권1호
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• pp.65-78
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• 2011

In the continuous review (Q, r) model one continuously monitors inventory level and places a replenishment order when the inventory position reaches the reorder point. In many business practices, however, inventory decreases in a discrete fashion. As a result, replenishment orders are usually placed after the inventory position gets far below the reorder point. This makes a chance of shortage more likely and the service level lower than designed. Such a discrepancy can be compensated for by raising the reorder point to some extent. The question is how much the reorder point should be raised in order to compensate for a potential shortage. In this study, we present experimental analyses for this question. Regression models are also proposed for on-site use.

• 한국경영과학회지
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• 제31권2호
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• pp.99-112
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• 2006

In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase amount constraint. And also, if we order at a certain date which was set by administrative convenience, we have capacity constraint to order the consolidated order demands (capacity constraint). We show this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invent a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.

• 산업경영시스템학회지
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• 제37권1호
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• pp.141-150
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• 2014

Due to their accessibility and 24-hr availability, convenience stores are an integral part of daily lives. Because they sell a limited number of products and have small shelf space, shelf space allocation and inventory replenishment are important considerations for inventory management that critically affect profit. In this paper, we propose five solutions for the vendor-managed inventory problem of convenience stores that maximize profit while considering stock-out-based product substitutions. The performance of the proposed solutions is evaluated via simulation to reflect the demand uncertainty and marketing activity.

• 한국시뮬레이션학회논문지
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• 제20권2호
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• pp.19-27
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• 2011

본 연구에서는 스무딩된 주문정책이 리드타임, 만족율, 재고비용에 미치는 영향을 연구한다. 이를 위해 스무딩된 order up to 주문정책을 사용하는 하류업체와 make to order 방식을 사용하는 상류업체로 구성된 공급사슬을 사용한다. 스무딩을 하면 리드타임이 예상하는 바와 같이 감소된다. 그러나 스무딩에 의해 하류업체에서의 만족율이 감소하며 재고비용이 증가된다. 한편 상류업체 제조시간의 분산이 평균 제조시간보다 만족율 및 재고비용에 미치는 영향이 더 크므로, 상류업체 제조시간의 변동성을 최소화해야 한다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.179-186
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• 2006

There was a lot of research to integration of the transshipment and inventory problem in supply chain. Such a integration of inventory and transshipment problem called IRP (Inventory Routing Problem). We consider a distribution problem in which a set of products has to be shipped from a supplier to several retailers in a given planning horizon. Transshipment from the supplier to the retailer is performed by vehicles of limited capacity. Each retailer determines replenishment leadtime and order quantity with buffer management. A supplier determines optimal vehicle routing in supply chain. We suggest a heuristic algorithm which be used TOC buffer management in a replenishment problem and a tabu search algorithm in VRP (Vehicle Routing Problem).

• 한국경영과학회지
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• 제29권3호
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• 대한산업공학회지
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• 제36권1호
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• pp.7-12
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• 2010

This paper considers a dynamic lot-sizing problem with backlogging under a minimum replenishment policy. For general concave production costs, we propose an O($T^5$) dynamic programming algorithm. If speculative motive is not allowed, in this case, a more efficient O($T^4$) algorithm is developed.