• Journal of the Korea Society for Simulation
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• v.12 no.4
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• pp.1-15
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• 2003

To satisfy and respond quickly to customers' demand, many companies are now aggressively focusing on supply chain management in order to strengthen their competitiveness. The modeling and analysis of supply chain environment have been widely studied. This study is concerned with the development of supply chain simulator which deals with stochastic natures existing in the supply chain environment. We proposed the mathematical model for the efficient cost analysis and developed the supply chain simulator based on the proposed mathematical model with object-oriented language C++. The simple experiment which find the best combination of policies considering the whole cost shows the possibility and reasonability of the developed simulator.

• Industrial Engineering and Management Systems
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• v.13 no.3
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• pp.319-329
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• 2014

Supply chain management is a subject that has an increasing importance due to the developments in the global markets and technology. In this paper, a fuzzy multi-objective linear programming model is developed for the supply chain of a company dealing with procurement, storage, filling, and distribution of liquefied petroleum gas (LPG) in Turkey. The model intends to determine the quantities of LPG to be procured, stored, filled to cylinders, and transported between the plants and demand centers for six planning periods. In this model, which aims to minimize both total costs (sum of procurement, storage, filling, and transportation costs) and total transportation distances, demand quantities of the main demand centers and decision maker's aspiration levels about objective functions are fuzzy. After comparing the results obtained from the model with those obtained by using different methods, it is concluded that the proposed method can be applied to real world problems practically and it may be used in this type of problems in order to generate an efficient solution.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.157-175
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• 2011

The purpose of this paper is to find out the effects of the gambler's fallacy bias on the supply chain. For this study, the simulation was based on a casual structure of the Beer Distribution Game from Sterman(2000)'s Business Dynamics and designed into 2 different models : the first model carries the exact same structure as the reference mentioned above and for the second model, the comparison model is used reflecting gambler's fallacy bias. Each model has 2 different demand patterns. The 4 cases of models was tested with 1,000 different random number seeds. The results for the simulation are following : In the aspect of the inventory and out of stock, the basic model resulted better than the comparison. However, in the bullwhip effect, the comparison model has less than the basic in terms of the level demand pattern. But there was no significant difference in the cycle demand.

• 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 Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.9-21
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• 2004

Semiconductor industry is the one whose supply chain network is distributed all over the world. And it has different characteristics with other manufacturing industries as reentrancy, binning, substitution. In this paper, we suggest supply chain models for the semiconductor industry, consisting of production and distribution chains, where manufacturing characteristics are considered. Three policies for the production chain and two policies for the distribution chain are suggested and formulated mathematically. Six combination policies are tested for the evaluation of performances with example. It is shown that the supply chain is operated, if production and distribution are coordinated and managed based on the demand information, without inventory, as efficiently as the chain with inventory.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.41-51
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• 2013

Tendency for small changes in end-consumer demand to be amplified as one moves further up the supply chain is known as bullwhip effect (BE). BE is usually defined as variance(order)/variance(demand). Since such distorted information throughout the supply chain can lead to inefficiencies, many studies to reduce variance(order) have been performed. However, in this study, we show that minimization of BE may increase inefficiencies of the supply chain. We introduce a new objective function to increase system efficiency using smoothed ordering policies. Simulation optimization is utilized to find optimal smoothed ordering policies.

• Korean System Dynamics Review
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• v.9 no.2
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• pp.5-25
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• 2008

This paper analysed the impact of return policy as a coordination mechanism for decentralized supply chain with one capacitated supplier and two competing retailers under random demand distribution. In this study, Shortage gaming also considered to reflect a competing environment of two retailers. System dynamics approach was used to model the baseline two echelon supply chain and return policy on it. Given each of 4 experiment settings being used for 100 simulations with different random seeds, 400 random samples were used in a t-test. The result show that return policy significantly enhance the supply chain profits and fillrates. The analysis suggest that the supply chain performance can be build up by implementing a return policy even though under consideration of a capacitated supplier and competing retailers.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.21-35
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• 2014

As productions and deliveries of multiple products to multiple marketplaces have been increasingly popular, supply chain flexibility, which refers to an ability to deal with demand and capacity uncertainty, becomes an important issue in supply chain management. However, logistics costs have been largely neglected in the literature on supply chain flexibility structure. In this paper, we propose mathematical models to investigate the impact of the logistics costs on the optimal flexibility structure. We also conduct a simulation study and observe that logistics costs have a significant impact on the decision on supply chain flexibility structure. Such conclusion is also supported by the case study of a global car manufacturer, Honda Motors.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.39-47
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• 2006

In most of supply chain planning practices, the estimated demands, which are forecasted for each individual period in a forecasting window, are regarded as deterministic. But, in reality, the forecasted demands for the periods of a given horizon are stochastically distributed. Instead of using a safety stock, this study considers a direct control of service level by choosing the demand used in planning from the distributed forecasted demand values for the corresponding period. Using the demand quantile and echelon stock concept, we propose a simple but efficient heuristic algorithm for multi-echelon serial systems under service level constraints. Through a comprehensive simulation study, the proposed algorithm was shown to be very accurate compared with the optimal solutions.

• Korean Management Science Review
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• v.29 no.1
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• pp.153-168
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• 2012

Order allocation is one of the most important decision-making problems of firms having significant influences on performances of themselves and the whole supply chain. Existing researches about order allocation have mainly focused on evaluating capabilities of directly connected suppliers so that it is hard to consider effects and interactions from undirected connections over multiple lower-layers. To alleviate the limitation, this paper proposed a novel approach to order allocation using structural hole. By applying the concept of structural hole to the supply network, we could evaluate the structural supplying powers of firms with respect to both of direct and indirect connections. In the proposed approach, we derived a methodology to measure the potential supplying power of each firm by modifying the effective size as one of the measurements of structural hole and then, proposed its application, the structural hole based order allocation strategy. Furthermore, we conducted the agent based modeling of supply chain to perform the decision-making process of order allocation and simulated the proposed strategy. As a results, by coping with the variance of demand more stably, it could improve the performance of supply chain from the aspects of fill rate, inventory level and demand-supply balance.