• IE interfaces
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• v.21 no.4
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• pp.354-364
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• 2008

This paper deals with a design problem of simulation for MIME (multi indenture and multi echelon) with lateral transshipment. Especially, we consider lateral transshipments in case that (S-1, S) ordering policy is used in multi echelon repair system. Some rules for ordering spare parts in lateral transshipments between the lowest-level units are studied and are implemented by an activity diagram in object-oriented method. By numerical examples, we compare regular (S-1, S) ordering policy and (S-1, S) policy with lateral transshipment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.636-647
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.159-165
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• 2003

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. Since it has been known that traditional reorder policies sometimes show poor performance in distribution systems, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately f3r the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value fur general multi-echelon systems is very complex, we provide two approximation methods. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• IE interfaces
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• v.17 no.3
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• pp.359-374
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2- echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Journal of the Korea Society for Simulation
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• v.10 no.1
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• pp.35-50
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• 2001

Managing multi-echelon inventory systems has gained importance over the last decade mainly because integrated control of supply chains consisting of several processing and distribution stages has become feasible through modern information technology. Determination of optimal inventory policy for multi-echelon supply chain is made difficult by the complex interaction between the different levels. In this paper, we investigate performance of five inventory policies (fixed quantity order policy, fixed interval order policy, compromised order policy, lead time-fixed quantity order policy, and mixed order policy) in a multi-echelon supply chain by using a simulation model constructed with AweSim simulation language. The results of the simulation study show that the mixed order policy is the best among five inventory policies in the most test problems except the case when the stockout cost per unit is much higher than the inventory holding and transportation costs per unit.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.133-138
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• 2006

The problem that we address is to determine the inventory stockage levels in a multi-echelon inventory system for repairable items in a multi-indenture system. We propose the simulation optimization approach to determine the stockage levels at each echelon, where a simulator for the underlying system is combined with an appropriate optimization tool, Genetic Algorithm (GA).

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.115-123
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• 2006

The main focus of this study is to investigate the performance of a clark-scarf type multi-echelon serial supply chain operating with a base-stock policy and to optimize the inventory levels in the supply chains so as to minimize the systemwide total inventory cost, comprising holding and backorder costs as all the nodes in the supply chain. The source of supply of raw materials to the most upstream node, namely supplier, is assumed to have an infinite raw material availability. Retailer faces random customer demand, which is assumed to be stationary and normally distributed. If the demand exceeds on-hand inventory, the excess demand is backlogged. Using the echelon stock and demand quantile concepts and an efficient simulation technique, we derive near optimal inventory policy. Additionally we discuss the derived results through the extensive experiments for different supply chain settings.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.77-83
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• 1996

The design of multi -echelon distribution system is need for appropriate inventory control strategy considering for systematic tradeoff between trunk cost in central warehouse and inventory cost in regional warehouse. This study presents a method of the efficient inventory control of multi-echelon distribution system through partial leadtime management.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.1
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• pp.63-72
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• 1990

This problem in this paper concerns the determination of safety stock for multi-echelon invenetory system. In this model the criterion is to minimize system safety stock subject to a service level constraint and expected annual total cost. Then, safety stock is determined by minimizing expected annual total cost and satisfying given service level. This expected annual total cost is obtained by expected total inventory holding cost plus the expected total stockout cost. Numerical example is given in a three-echelon inventory system. The results obtained by the use of the Hill Algorithm.

• Journal of the military operations research society of Korea
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• v.32 no.1
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• pp.113-132
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• 2006

This study suggested a readily applicable model to estimate the proper purchasing amount and the optimal CSP(Concurrent Spare Parts) inventory level based on a supporting echelon. For this model to be implemented, it is determined for studies about Multi-echelon Inventory Model to be divided by issues and utilized in the system Moreover, the model also includes the factors that are to be excluded for a reasearch purpose and to be simply assumed. Compared to previous studies, this model is to be considered the most possible factors, realistically designed, and practically used. It is claimed that the results of this model would raise an issue of improving traditional approaches in CSP acquisition and inventory management.