• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.93-100
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• 2023

In this paper, an alternative inventory policy that trades off the bullwhip effect at an upstream facility with cost minimization at a current facility, with the goal of reducing system wide total expected inventory costs, when external demand distributjon is autocorrelated, is considered. The alternative inventory policy has a form that is somewhere between one that completely neglects the autocorrleation and one that actively utilizes the autocorrelation. For this purpose, a mathematical model that allows us to evaluate system wide total expected inventory costs for a periodic review system is developed. This model enables us to identify an optimal inventory policy at a current facility that minimizes system wide total expected inventory costs by the best tradeoff of the bullwhip effect at an upstream facility with cost minimization at a current facility. From numerical experiments, it has been found that (i) when the autocorrelation is negative, the optimal policy is one that actively utilizes the autocorrelation, (ii) when the autocorrelation is small and positive, the optimal policy is one that neglects the autocorrelation, and (iii) when the autocorrelation is large and positive, the optimal policy is somewhere between one that actively utilizes the autocorrelation and one that neglect the autocorrelation.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.382-392
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• 2006

Vendor-managed inventory policy(VMIP) is a supply-chain initiative where the supplier is authorized to manage inventories of items at retail locations. In VMIP, the supplier monitors sales and stock information at retail locations and makes decisions of inventory replenishment and transportation simultaneously. VMIP has been known as an effective supply chain strategy that can realize many of benefits obtainable only in a fully integrated supply chain. However, VMIP does not always lead to lower the supply chain cost. It sometimes generates the total supply chain cost higher than the traditional retailer-managed inventory policy (RMIP). In this paper, we perform a comparison study on RMIP and VMIP in the retail supply chain which consists of a single supplier and a number of retailers. We formulate mixed integer programming models for both RMIP and VMIP with vehicle routing problems and perform computational experiments on various test problems. Furthermore, we derive the conditions which guarantee the dominant position for VMIP with respect to total supply chain cost in the simple retail supply chain.

• Korean Management Science Review
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• v.25 no.1
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• pp.107-121
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• 2008

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1-7
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• 2003

This paper considers an Integrated one-vendor multi-buyer production-inventory model where the vendor manufactures multiple products In lot at Her associated finite production rates In the model. It is allowed for earth product to be shipped In lot to the buyers before the whole product production is not completed yet. Each product lot is dispatched to the associated buyer In a number or shipments. The buyers consume their products at fixed rates. The objective is to the production and shipment schedules in the Integrated system. which minimizes the mean total annual cost per unit time. The mean total annual cost consists or production setup cost inventory holding cost and shipment cost. For the model, an Iterative optimal solution procedure with shipment consolidation policy incorporated is derived. It is then tested through numerical experiments to show how efficient and effective He shipment consolidation policy is.

• Journal of the Korean Operations Research and Management Science Society
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• v.1 no.1
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Journal of Korean Institute of Industrial Engineers
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• v.11 no.1
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• pp.41-49
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• 1985

This paper studies the two supplier inventory system in which order-level inventory policy with constant leadtimes is adopted. An optimal ordering policy to achieve the expected minimum total inventory cost is found by utilizing the concepts of the equivalence relation. Sensitivity analysis of the system parameters, the replenishment cost and the unit price, is done through a numerical example.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.153-160
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• 1995

This paper presents the parallel-type inventory structure using an order-up-to level inventory control system for analyzing the approximation of the expected units backordered and the measure of service. The rate of total expected backorders which is the measure of disservise, is given by dividing the improved units of total expected backorder into the total demand during an order cycle. the average annual total cost in system is obtained by considering the results. Total backorder model for the system without redistribution and the system with redistribution is described.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.93-98
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• 2009

This paper studies that $\sigma$ values(10, 20, 50) and $\rho$ values(-0.6, -0.3, 0.0, 0.3, 0.6) affect the total inventory cost of a supply chain and order fill rate when the market demand process follows a general auto-correlated AR(1) process without seasonality. $\sigma$ indicates the degree of demand fluctuation and $\rho$ means the trend of demand. ANOVA tests using a 5% significance level are performed in SPSS to examine significant performance changes among various cases.

• Journal of the military operations research society of Korea
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• v.18 no.2
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• pp.181-191
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• 1992

In this paper in order to prevent break of operation of equipments resulted from the delay of parts supply, the continuous review(Q, r) inventory model with probabilistic lead time is developed. If the lead tire is random varivable, the cycle also is stochastic. Then it is not easy to obtain the total cost equation of this inventory model. Therefore it is assumed that one cycle is the interval of reorder points. When the lead time is assumed to have exponential probability distribution, the lot-size and reorder point which minimize total cost are obtained. And as the lead time increases, the order quantity and the total cost are greater, but the reorder point increases by a certain point of time and then decreases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.25-34
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• 2011

In this paper, we investigate an inventory system where a single manufacturer purchases and processes raw materials in order to deliver finished goods to multiple retailers. Earlier study in this type of supply chain only consider a single raw material in order to produce finished goods, but we consider multi-raw materials in order to produce finished goods. Also, we develop an iterative solution procedure to find the order quantity for the finished goods and raw materials, and the number of shipments between manufacturer and retailers that minimizes the total cost per unit time of the raw materials ordering and holding, manufacture's setup and finished goods holding, the retailer's ordering and inventory holding. Numerical examples are presented to illustrate that jointly considering the total cost results in less total cost than that of considering them separately.