• 한국시뮬레이션학회논문지
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• 제20권2호
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• pp.19-27
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• 2011

본 연구에서는 스무딩된 주문정책이 리드타임, 만족율, 재고비용에 미치는 영향을 연구한다. 이를 위해 스무딩된 order up to 주문정책을 사용하는 하류업체와 make to order 방식을 사용하는 상류업체로 구성된 공급사슬을 사용한다. 스무딩을 하면 리드타임이 예상하는 바와 같이 감소된다. 그러나 스무딩에 의해 하류업체에서의 만족율이 감소하며 재고비용이 증가된다. 한편 상류업체 제조시간의 분산이 평균 제조시간보다 만족율 및 재고비용에 미치는 영향이 더 크므로, 상류업체 제조시간의 변동성을 최소화해야 한다.

• 대한산업공학회지
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• 제34권1호
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• pp.1-12
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• 2008

The Kanban system in Just-In-Time (JIT) production is very effective in reducing the inventories when consumption rate of the final product is relatively stable. When large fluctuations exist in the consumption rate, a new production ordering policy in which the production order quantity is determined by smoothing the demands exponentially is more suitable. This new ordering policy has not been investigated sufficiently. In this research, a multi-stage production and inventory system with stock points for materials and finished items located at each stage is considered. Approximations of average inventories at each stage in the system are derived theoretically. Numerical simulations are carried out to assess the accuracy of approximations and to evaluate the effectiveness of the new ordering policy as compared with the Kanban system. As a result, it is shown that the new ordering policy can achieve significantly lower inventory costs than the original Kanban system. The new ordering policy thus emerges as a key concept for an effective supply chain management.

• 한국시뮬레이션학회논문지
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• 제22권2호
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• pp.41-51
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• 2013

하류업체에 발생하는 소비자 수요의 조그만 변화가 상류업체로 올라갈수록 증폭되는 현상을 채찍효과(BE)라 한다. BE는 일반적으로 주문량 분산/수요량 분산으로 정의된다. 이와 같이 왜곡된 정보는 공급사슬의 비효율성을 유발하므로, 주문량의 분산을 줄이는 많은 연구들이 수행되고 있다. 그러나 본 연구에서는 BE를 최소화하는 것이 오히려 공급사슬의 비효율성을 증가시킬 수 있음을 보여 주며, 스무딩된 주문 정책을 사용하여 공급사슬의 효율성를 증가시키기 위한 새로운 목적함수를 설정한다. 최적화된 스무딩 주문정책을 연구하기 위해 시뮬레이션 최적화 기법을 사용한다.

• 한국시뮬레이션학회논문지
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• 제12권3호
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• pp.31-40
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• 2003

This paper studies an optimal policy for a certain class of (s, S) inventory control systems, where the demands are characterized by the renewal arrival process. To minimize the average cost over a simulation period, we apply a stochastic optimization algorithm which uses the gradients of parameters, s and S. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. The optimal estimates of s and S from our simulation results are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and inter-arrival times of demands. Another direction involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• 한국시뮬레이션학회논문지
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• 제12권2호
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• pp.1-11
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• 2003

In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).