• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.44-51
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• 2017

In today's competitive environment, supply chain management is a major concern for a company. Two of the key issues in supply chain management are transportation and inventory management. To achieve significant savings, companies should integrate these two issues instead of treating them separately. In this paper we develop a framework for modeling stochastic programming in a supply chain that is subject to demand uncertainty. With reasonable assumptions, two stochastic programming models are presented, respectively, including a single-period and a multi-period situations. Our assumptions allow us to capture the stochastic nature of the problem and translate it into a deterministic model. And then, based on the genetic algorithm and stochastic simulation, a solution method is developed to solve the model. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.349-357
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using houristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.

• Journal of Digital Convergence
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• v.5 no.1
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• pp.47-53
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using heuristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.1-17
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• 2017

This study investigates a buyer-supplier supply chain, in which a buyer delegates the production process to a supplier as in many practices. The consumer's buying intention and overall supply chain performance are affected not only by the buyer's decision on sales price but also by the supplier's decision on product quality. Therefore, the buyer has a motivation to control the supplier's quality investment. Among various incentive schemes that the buyer can adopt in practice, we consider a revenue-sharing contract and investigate its unique characteristics. By comparison with a typical wholesale price contract, we reveal that the revenue-sharing contract can enhance supply chain's overall performance, including quality, demand, and profits of not only overall supply chain but also each player. We contribute to the academia and the supply chain practice by providing important guidelines in adopting incentive schemes and effectively managing product quality in a supply chain.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.51-57
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• 2006

Recently, youth unemployment is not a mere economic problem in Korea. It could be developed into a serious social problem. It has been long since youth unemployment rate was more than double in total unemployment rate, which stood at 3.5 percent in 2005 and then the inactivity among the younger job-seekers is appearing to be chronic. Hence, this paper examines the status and causes of the youth unemployment problem and studies the possibility to apply the Demand-Supply Chain Management to the problem.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.103-111
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• 2013

As the demand-oriented management has been getting important in Supply Chain Management (SCM), various forecasting methods have been suggested including regression analyses. However, dependency structures among variables have been captured by a correlation coefficient, only. It results in inaccurate demand predictions. This paper suggests a new and effective forecasting modeling framework using student's t-copula function. In order to show overall modeling procedures framework, heavy tail typed numerical data and its copula estimations are provided. The suggested methodology can contribute to decrease the bullwhip effect and to stabilize volatile environment in a supply chain network.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.658-663
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• 2005

This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.

• 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.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.129-158
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• 2015

It is necessary for retailers to determine the optimal ordering policy of products considering supply disruptions due to a natural disaster and a production process failure as quality and machine breakdowns. Under the situation, a dualsourcing supply chain (DSSC) is one of effective SC for retailers to order products reliably. This paper proposes the optimal ordering policy of a product in a DSSC with a retailer and two manufacturers. Two manufacturers may face supply disruptions due to a natural disater and a production process failure after they received the retailer's order of products. Here, two scenarios of demand information of products are assumed: (i) the demand distribution is known (ii) mean and variance of the demand are known. Under above situations, two types of DSSC are discussed. Under a decentralized DSSC (DSC), a retailer determines the optimal ordering policy to maximize his/her total expected profit. Under the integrated DSSC (ISC), the optimal ordering policy is determined to maximize the whole system's total expected profit. Numerical analysis investigates how demand information and supply disruptions affect the optimal decisions under DSC and ISC. Besides, profitability of supply chain coordination adjusting the wholesale price is evaluated to encourage the optimal decision under ISC.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.734-741
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• 2002

The importance of efficient Supply Chain Management is increasing in accordance with recent industrial environment, such as globalization of business, complexity and diversity of company's management structure, and variety of customer's demand. In a rapidly changed environment of business, quick and efficient decision making is the important matter to the survival of the company. The purpose of this study supports decision making for efficient supply chain management. In this study, we consider simultaneously and mutually reflecting the preference of each constituent (Supplier, Manufacturing plant, Distribution center, Customer) on supply chain network, and decide company's strategic choice and coordinated production/distribution models of company. The Analytical Hierarchy Process is used for decision making of qualitative and quantitative elements. We use the results of AHP as inputs and propose mathematical models thru Mixed Integer Programming.