• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.125-138
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• 2006

This paper considers a periodic review, two-echelon inventory system with one central warehouse and several re-tailers facing normally distributed demand. The goal is to attain target fill rates, while the systemwide total holding costs are minimized. An important aspect of this problem is material rationing in the case of shortages. If a central warehouse has insufficient inventory to deliver all replenishment orders to retailers, all order quantities are should be adjusted according to some rationing rule. A simple but efficient rationing rule is proposed and compared with the Balanced Stock (BS) rationing as introduced by Heijden which is known to be the best rationing policy in the literature. Numerical results show that the proposed rationing rule is more cost effective than BS rationing, especially for the differences in holding costs between retailers are large.

• 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.12 no.1
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• pp.1-9
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• 1987

This paper considers (S -1, S) inventory models which have wide applications in reparable spare parts inventory systems and multi-echelon systems. We assume a discrete compounds Poisson demand and order size dependent delivery times ; when the replenishment order size is n, we assume the delivery time distribution is arbitrary with finite mean $b_{n}$ . On the basis of the fact the outstanding orders follow a certain queueing process, we introduce the results of Fakinos (1982). We develop the efficient recursive formulae to find the optimal $S^{*}$ under several performance measures as a function of the decision variable S. The results of this paper can be applied to the multi-echelon systems such as MEETRIC.C.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.146-158
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• 2004

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives in a stationary Poisson process. The problem is formulated using METRIC-approximation in a combined approach of pricing and (S-l, S) inventory policy, for which a heuristic solution algorithm is derived with respect to the corresponding one-warehouse multi-retailer supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed with two cases. The first case deals with identical retailers and the second case deals with different retailers with different market sizes. The computational results show that the proposed algorithm is efficient and derives quite good decisions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.362-372
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• 2008

Manufacturers, or vendors, and their customers continue to adopt vendor-managed inventory(VMI) program to improve supply chain performance through collaboration achieved by consolidating replenishment responsibility upstream with vendors. In this paper, we construct a mixed integer linear programming model and propose a genetic algorithm for the integrated inventory and routing problems with lost sales maximizing the total profit in the VMI supply chains which comprise of a single manufacturer and multi-retailer. The proposed GA is compared with the mathematical model on the various sized test problems with respect to the solution quality and computation time. As a result, the GA demonstrates the capability of reaching solutions that are very close to those obtained by the mathematical model for small problems and stay within 3.2% from those obtained by the mathematical model for larger problems, with a much shorter computation time. Finally, we investigate the effects of the cost and operation variables on the total profit of the problem as well as the GA performance through the sensitivity analyses.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.170-179
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• 2016

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material. In the experimental implementation of our rule-based inventory planning, Company 'S' reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker's continuing support and attention even without seeing any upcoming business crisis.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.88-91
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• 2012

Joint optimization of preventive age replacement and inventory policy is considered in this paper. There are three decision variables in the problem: (i) preventive replacement age of the operating unit, (ii) order quantity per order and (iii) reorder point for spare replenishment. Preventive replacement age and order quantity are jointly determined so as to minimize the expected cost rate, and then the reorder point for meeting a desired service level is found. A numerical example is included to explain the joint optimization model.

• Journal of Korean Institute of Industrial Engineers
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• v.9 no.2
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• pp.37-46
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• 1983

The classical deterministic inventory model is investigated for the case of linear trend in demand and constant production rate. Three models are presented so as to minimize the total of set-up and inventory carrying costs over a finite time span. For each of the policies the methods are developed which can determine the optimal production quantities and times at which production should be started. Three policies are compared in point of costs and times for getting solutions and various case examples are also presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.3
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• pp.91-105
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• 2011

In this paper, we analyze a logistic system involving a supplier who produces and delivers multiple types of items and a buyer who receives and sells the products to end customers. The buyer controls the inventory level by replenishing each product item up to a given order-up-to-level to cope with stochastic demand of end customers. In response to the buyer's order, the supplier produces or outsources the ordered item and delivers them at the start of each period. For the system described above, a mathematical model for a single type of item was developed from the buyer's perspective. Based on the model, an efficient method to find the cycle length and safety factor which correspond to a local minimum solution is proposed. This single product model was extended to cover a multiple item situation. From the model, algorithms to decide the base cycle length and order interval of each item were proposed. The results of the computational experiment show that the algorithms were able to determine the global optimum solution for all tested cases within a reasonable amount of time.