• 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.

• 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.

• 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.

• Korean Management Science Review
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• v.28 no.1
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• pp.117-127
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• 2011

In the Multi-Echelon maintenance environment, METRIC(Multi-Echelon Technique for Repairable Item Control) has been used in several different inventory level selection models, such as MOD-METRIC, Vari-METRIC, and Dyna- ETRIC. While this model's logic is easy to be implemented, a critical assumption of infinite maintenance capacity would deteriorate actual values, especially Expected Back Order(EBO)s for each item. To improve the accuracy of EBO, we develop two models using simulation and queueing theory that calculates EBO considering finite capacity. The result of our numerical example shows that the expected backorder from our model is much closer to the true value than the one from Vari-METRIC. The queueing model is preferable to the simulation model regarding the computational time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.61-68
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• 2019

Currently many companies are interested in reduction of the carbon emissions associated with their supply chain activities such as transportation and operations. Operational decisions, such as modifications in order quantities could an effective way in reducing carbon emissions in the supply chain. Cap-and-trade regulation, sometimes called emissions trading, is a market-based tool to limit greenhouse gas emissions. Under cap-and-trade regulation, emission credits are allocated to the firms and the firms trades emissions under cap-and-trade schemes. In this paper, we propose a single-manufacturer single-buyer two-echelon supply chain problem under the cap-and-trade mechanism incorporating the carbon emissions caused by transportation and warehousing activities where a single manufacturer produces a family of items in order to deliver a family of items to a single buyer at a fixed interval of time for effective implementation of Just-In-Time (JIT) Purchasing. An integrated multi-product lot-splitting model of facilitating multiple shipments in small lots between buyer and manufacturer is developed in a JIT Purchasing environment. Also, an iterative heuristic algorithm is developed to derive the common order interval, the number of intervals for each product and the number of shipments between the buyer and the manufacturer during the common interval. A numerical example is given to illustrate the savings in reduction of total cost and carbon emissions by the inventory model incorporating cap-and-trade mechanism compared to the classical inventory model. The proposed inventory model could be useful for the practical solution of two-echelon supply chain inventory problem under cap-and-trade mechanism.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.742-749
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• 2002

This paper deals with a continuous-review two-echelon inventory model with one-for-one replenishment and Poisson demand where transshipments among retailers are allowed. Two classes of inventory systems are considered by the number of distribution centers(DCs) which provide each retailor with inventory items. 1:N class inventory system and M:N class inventory system respectively. Two-phase model is constructed to find out the optimal inventory positions which minimize supply chain costs. Approximations for customer service levels of the system are evaluated in the first phase, and the optimal inventory positions are found subject to the constraints for service level in the second phase. Simulation tests are performed to assure the effectiveness of the proposed model. The effect of transshipment is evaluated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.110-116
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• 2008

Operational strategy for inventory control in the distribution system has been given attention. If an individual enterprise implements the strategy, it is not easy to gain scale merits because of limited quantity or burden of inventory. In this study, we propose an operational strategy for inventory control that considers managerial integration of regional distribution centers (RDCs) and present a model of it. In a network of several RDCs, they could share inventory information and supply parts for others in case of an inventory shortage. And a numerical example of the network is illustrated, which compares two operational strategies, integration management of RDCs and individual management of them. The result shows total cost reduction in the strategy of integration management through the efficient inventory control of multi-echelon distribution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.441-445
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• 2004

In this paper, we deal with an inventory model of a multi-stage, serial supply chain system where a single product type and nonstationary customer demand pattern are considered. The retailer and suppliers place their orders according to an echelon-stock based replenishment control policy. We assume that the suppliers can access online information on the demand history and use this information when making their replenishment decisions. Using a reinforcement learning technique, the inventory control parameters are designed to adaptively change as the customer demand pattern is altered, in order to maintain a given target service level. Through a simulation based experiment, we verified that our approach is good for maintaining the target service level.

• 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.