• 한국경영과학회지
• /
• 제30권3호
• /
• pp.81-93
• /
• 2005

This paper models supply chain uncertainties in the dynamic Newsboy Problem context. The system consists of one supplier and one retailer who place an order to the supplier every period. Demand uncertainty is modeled as stochastic period demand, and supply uncertainty as the uncertainty in quantities delivered by the supplier. The supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of $(1-\beta)$ We formulate the problem as a dynamic programming problem and derive the first-order optimality condition. Through a numerical study, we measure the extent to which the cost decrease due to the reduction in supply uncertainty depends on the level of demand uncertainty. One of the most important findings In this paper is that this cost decrease is relatively small if demand uncertainty is kept high, and vice versa. We also backup this numerical result by analyzing the distribution of ending Inventory under the supply and demand uncertainties.

• 전기학회논문지
• /
• 제63권11호
• /
• pp.1503-1510
• /
• 2014

This study organizes scenarios on the power supply plans and electricity load forecasts considering their uncertainties and estimates natural gas quantity for electricity generation, total electricity supply cost and air pollutant emission of each scenario. Also the analysis is performed to check the properness of government's natural gas demand forecast and the possibility of achieving the government's CO2 emission target with the current plan and other scenarios. In result, no scenario satisfies the government's CO2 emission target and the natural gas demand could be doubled to the government's forecast. As under-forecast of natural gas demand has caused the increased natural gas procurement cost, it is required to consider uncertainties of power plant construction plan and electricity demand forecast in forecasting the natural gas demand. In addition, it is found that CO2 emission target could be achieved by enlarging natural gas use and demand-side management without big increase of total costs.

• 한국산학기술학회논문지
• /
• 제11권9호
• /
• pp.3304-3310
• /
• 2010

연구는 가격 및 수요 불확실성하의 강건한 (robust) 생산 및 수송 전략을 수립함으로써 수요 및 가격 불확실성이 존재하는 TFT-LCD 제조업 공급사슬망의 의사결정 문제를 해결하고자 한다. 품질로 구분되는 제품들의 생산, 재고 및 물류에 관한 의사결정을 조정하기 위해, 본 연구에서는 생산용량 제약, 해상/항공 수송 리드타임 및 용량 제약 등의 현실적인 제약조건들을 반영하는 확정적 모델을 정의하고, 시나리오 모델을 이용하여 수요 및 가격 불확실성을 함께 반영하는 확률적 혼합정수선형계획법모형들을 개발한다. 또한 개발된 확률적 모형들의 robust 솔루션을 도출하기 위한 휴리스틱 알고리즘을 제안한다. 그리고 이들 모형들로부터 산출된 솔루션의 성능을 실험을 통하여 다양한 시나리오 하에서 평가하도록 한다.

• 반도체디스플레이기술학회지
• /
• 제22권2호
• /
• pp.104-111
• /
• 2023

The semiconductor industry, which relies on global supply chains, has recently been facing longer lead time for material procurement due to supply chain uncertainties. Moreover, since increasing customer satisfaction and reducing inventory costs are in a trade-off relationship, it is challenging to determine the appropriate safety stock level under demand and lead time uncertainties. In this paper, we propose a framework for determining safety stock levels by utilizing the optimization method to determine the optimal safety stock level. Additionally, we employ a linear regression method to analyze customer satisfaction scores and inventory costs based on variations in lead time and demand. To verify the effectiveness of the proposed framework, we compared safety stock levels obtained by the regression equations with those of the conventional method. The numerical experiments demonstrated that the proposed method successfully reduces inventory costs while maintaining the same level of customer satisfaction when lead time increases.

• 산업경영시스템학회지
• /
• 제40권4호
• /
• pp.29-37
• /
• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• 경영과학
• /
• 제33권3호
• /
• pp.105-117
• /
• 2016

In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.

• 상하수도학회지
• /
• 제25권3호
• /
• pp.293-305
• /
• 2011

A special concern is paid to the risks with which small-sized water resources systems are confronted in supplying water in the far future. Taking the Gwangdong dam reservoir as a case study, the authors seek to understand demand-side and supply-side disturbances of a reservoir, which, respectively, corresponds to effects of water demand changes on the intake amount and those of climate changes on the inflow amount. In result, it is demonstrated that both disturbances in the next 50 years are almost unpredictable. Yet the projection ranges, thought of as relatively reliable information that models offer, reveal that severity and period of water shortage is very likely to change. It is therefore concluded that water resources management requires more rigorous approaches to overcoming high uncertainties. The methods and models for projecting those disturbances are selected, based on practicality and applicability. Nevertheless, they show a large usefulness, especially in dealing with data shortage and reducing the needs for expensive modeling resources.

• 한국시스템다이내믹스연구
• /
• 제13권1호
• /
• pp.81-112
• /
• 2012

This study investigate the impact of supply chain contracts on supply chain performance. This study employed Price adjustment contract(PAC) and Quantity adjustment contract(QAC) as two main types of a vertical coordination mechanism. We simulate different types of coordination mechanisms with various degrees of demand uncertainties and several capacity tightness scenarios. This study shows that PAC and QAC significantly enhance the supply chain profits and fill rates suggesting that supply chain performance can be improved by implementing a proper coordination mechanism depends on the level of a capacity tightness and demand uncertainty.

• 산업경영시스템학회지
• /
• 제44권4호
• /
• pp.220-226
• /
• 2021

In supply chain, there are a variety of different uncertainties including demand, service time, lead time, and so forth. The uncertainty of demand has been commonly studied by researchers or practitioners in the field of supply chain. However, the uncertainty of upstream supply chain has also increased. A problem of uncertainty in the upstream supply chain is the fluctuation of the lead time. The stochastic lead time sometimes causes to happen so called the order crossover which is not the same sequences of the order placed and the order arrived. When the order crossover happens, ordinary inventory policies have difficult to find the optimal inventory solutions. In this research, we investigate the lead time distribution in case of the order crossover and explore the resolutions of the inventory solution with the order crossover.

• 대한산업공학회지
• /
• 제31권2호
• /
• pp.106-119
• /
• 2005

Uncertainties inherent in customer demand patterns make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. In this paper, we propose two intelligent adaptive inventory control models for a supply chain consisting of one supplier and multiple retailers, with the assumption of information sharing. The inventory control parameters of the supplier and retailers are order placement time to an outside source and reorder points in terms of inventory position, respectively. Unlike most extant inventory control approaches, modeling the uncertainty of customer demand as a stationary statistical distribution is not necessary in these models. Instead, using a reinforcement learning technique, the control parameters are designed to adaptively change as customer demand patterns change. A simulation based experiment was performed to compare the performance of the inventory control models.