• Korean Management Science Review
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• v.10 no.2
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• pp.79-91
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• 1993

Strategic decisions related to the design of a physical distribution system can be classified into three basic components : facility location, transportation, inventory decisions. In this research the interdependence of those decisions are expressed in a mathematical model such that the total relevant cost of the system is minimized. We suggested a heuristic technique for solving the model. In broad terms, our solution technique combines a heuristic method for determining which candidate DCs to open and an exact method for minimizing costs given a set of open DCs. And we also developed a decision supporting package for the design of a physical distribution system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.222-244
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• 1990

A multi-echelon structure of manufacturing and distribution system in considered, where the raw materials are transformed into a finished good through a number to manufacturing echelons and it is distributed to the lower echelons(retailers, or customers). The raw material, work-in-process, finished good inventory and the distribution costs are unified into one model. The objective is to determine the ordering policy of raw materials, manufacturing lot size, the number of sub-batch and the distribution policy of the finished good which minimize the annual total system cost. A computer program for a heuristic search technique is developed, by which a numerical example is examined.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.226-226
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• 1993

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.145-157
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• 2005

There are a lot of raw materials, work-in-processes and finished goods in manufacturing industry. Here, the less stock of materials and work-in-processes manufacturing industry has, the worse the rate of the production is. Inversely, the more manufacturing industry has, the more expensive the cost to support them is. Thus, it is important for us to balance them efficiently. In general, inventory problems are to decide appropriate times to produce goods and to determine appropriate quantities of goods. Therefore, inventory problems require as more useful information as possible. For example, there are demand, lead time, ordering point and so on. In this paper, we deal with an optimal ordering policy on both way substitutable two-commodity inventory control system. That is, there is a problem of how to allocate the produced two kinds of goods in a factory to m areas so as to minimize the total expected inventory cost. The demand of each area is probabilistic, and we adopt the exponential distribution as a probability density function of demand. Moreover, we provide numerical examples of the problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.93-104
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• 2007

We consider a supply chain where products are shipped to warehouse from manufacturing system to customers. Products are supplied from either in-house regular manufacturing or the secondary source such as subcontractor. The inventory in warehouse is controlled by base-stock policy, that is, whenever a demand arrives from customer, an order is released to the manufacturing system. Unsatisfied demand is backlogged. The manufacturing system is modeled as M/M/s+1/c queueing system, and the orders exceeding the given limit care blocked and lost. The steady state distribution of the outstanding orders and the throughput of the manufacturing system are functions of the level of engagement In the secondary source. There is a profit obtained from throughput and cost not only due to the engagement of the secondary source in the manufacturing system but also inventory positions. We want to maximize the total production profit minus the total cost of the production system by simultaneously determining the optimal level of engagement of the secondary source and the optimal base-stock level of the inventory. We develop two algorithms : one without guarantee of the optimal solution but with the small number of computations, the other optimal but with more computations.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.121-127
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• 2007

CSP(Concurrent Spare Parts) is supplied with the procurement of new equipment or weapon system and is used to sustain the equipment without resupply during the initial coverage period. This study is concerned with a problem of determining the near optimal inventory level of the spare parts, especially Concurrent Spare Parts. For this, we utilize the mixed periodic and continuous review polices considering the CSP and (r,Q) Policies concurrently in a two-echelon distribution system. We propose the mathematical model to minimize the total cost which is composed with ordering cost, purchasing cost, holding cost, and stickout cost. If the mixed policy is compared to other policies(CSP, (r,Q)), the proposed methodology performs well and is best policy in the equipment maintenance expenses.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.101-105
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• 2002

In a traditional hierarchical inventory system, direct orders are the only information for inventory management that is exchanged between the firms involved. But due to the rapid development of modern information technology, it becomes possible for the firms to share more information in real time, e.g. demand and inventory status data. And so the term Supply Chain has emerged because it is seen as an important source of competitive advantage. Now it is possible to challenge traditional approaches to inventory management. In the past, one of the de-facto assumptions for inventory management was that the demand pattern follows a specific distribution function. However, it is undesirable to apply this assumption in real situations because the demand information in the supply chain tends to be distorted due to the bullwhip effect in a supply chain. To overcome this weakness, we propose a new solution method using NN (Neural Network). Our method proceeds in three steps. First, we find the patterns of optimal reorder points by analyzing past data. Second. train the NN using these pattern data and finally decide the reorder point. Using simulation experiment, we show that the proposed solution method gives better result than that of traditional research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.423-437
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• 2015

The IPv6 which solved the exhaustion problem of IPv4's IP address is going to be used for many kinds of industries. As a result, there are some products which can be connected to other connectable things, it called Internet of Things (IoT). With growing new propagated products including networking, each product can get an IP address of IPv6, which means it is possible that things also have their own IP addresses. Thus, IP address management system is more important and needs tracking and collecting system for unused products with IP addresses. This study suggests new distribution tracking and inventory management system for IoT products, which offers a current location of things and manages stocks in the warehouse with the static IP address and the location-based service.