• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.285-288
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• 1996

This paper deals with an (s, S) spare-part inventory model with general leadtime. In the model, if the inventory level falls to a reorder point s, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (s, S) minimizing the cost rate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.427-431
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• 1994

The objective of this paper is to provide an inventory control policy for the system that carries a single item with a multiple demand classes, when the demand is Poisson distributed random variable. The inventory control process includes the process of determining the reorder point, and the process of inventory control during the lead time. The goal of the optimization process is to achieve the service level of each demand class as well as the system-wide total service level at a preset desired service level while sustaining a minimum average inventory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.93-103
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• 1995

This paper des with an economic production quantity model with partial backorders for the situation in which production lead time is deterministic and demand during lead time follows a continuous distribution. In the model, an objective function is formulated In minimize an average annual inventory cost. And then the procedure of iterative solution method for the model is developed to find both production reorder point and production quantity. Finally, sensitivity analysis for various partial backorder ratios and standard deviations of demand during production lead time are presented.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.79-83
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• 1976

This paper deals with a computer simulation for the stochastic inventory system in which the decision rules are associated with the problem of forecasting uncertain demand, lead time, and amount of shortages. The model consists of mainly three parts; part I$\cdots$the model calculates the expected demand during lead time through the built-in subrou tine program for random number generator and the probability distribution of the demand, part II$\cdots$the model calculates all the possible expected shortages per lead time period, part III$\cdots$finally the model calculates all the possible total inventory cost over the simulation period. These total inventory costs are compared for searching the optimal inventory cost with the best ordering quantity and reorder point. An application example of the simulation program is given.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.44-49
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• 1996

This paper deals with a (Q, r) spare-part inventory model with gamma leadtime. In the model, if the inventory level falls to a reorder point r, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (Q, r) minimizing the cost rate. A numerical example is presented to explain the model.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.71-80
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• 1996

This paper presents a stochastic partial inventory model for the situation in which demand is deterministic, lead time follows normal distribution and backorder ratio during the stockout period decreases exponentially according to the length of backorder period. In this situation, an objective function is formulated to minimize the average annual cost, which is the sum of the ordering, carrying time-proportional backordering, quantity-proportional backordering and lost sales costs. And then the procedure of iterative solution method for the model is developed to find optimal reorder point and order quantity and numerical example to illustrate the proposed method is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.502-508
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• 2000

정보 시스템과 전자 상거래의 보편화로 실시간 판매 정보 공유가 용이하여짐에 따라, 공유 정보를 적절히 활용하는 재고 정책의 필요성이 증가하고 있다. 본 연구에서는 정보 공유 환경하의 one-warehouse multi-retailer 모델에서 개별 공유 정보를 보다 정확히 활용하여 재주문점 결정을 할 수 있는 방안을 제시하였다. 기존의 하위 계층의 재고량의 합에 기반하는 echelon stock policy 의 경우 상세 정보의 손실을 발생하는 문제가 있는 반면 본 연구에서는 개별 retailer 들의 재고량에 기반한 marginal savings의 개념을 정의하고, 이를 바탕으로 상세 정보에 기반한 재주문 정책을 제시하였다. 제시된 정책은 기존의 echelon stock policy 에 비해 우수한 결과를 나타냄을 실험을 통해 입증하였다.

• Journal of the Korean Operations Research and Management Science Society
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• v.11 no.1
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• pp.44-50
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• 1986

In this paper, we find optimal policy for the (Q, r) inventory model under the lead time uncertainty. The (Q, r) inventory model is such that the fixed order quantity Q is placed whenever the level of on hand stock reaches the reorder point r. We first develop the single level inventory model as the basis for the analysis multi-level distribution systems. The functional problem is to determine when and how much to order in order to minimize the expected total cost per unit time, which includes the set up, inventory holding and inventory shortage cost. The model, then, is extended to the multi-level distribution system consisting of the factory, warehouses and retailers. In this case, we also find an optimal policy which minimizes the total cost of the contralized multi-level distribution system.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.33-49
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• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.126-132
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• 2012

This paper deals with a centralized warehouse problem with multi-item and capacity constraint. The objective of this paper is to decide the number and location of centralized warehouses and determineorder quantity (Q), reorder point (r) of each centralized warehouse to minimize holding, setup, penalty, and transportation costs. Each centralized warehouse uses continuous review inventory policy and its budget is limited. A SA (Simulated Annealing) approach is developed and its performance is tested by using some computational experiments.