• 한국경영과학회지
• /
• 제34권4호
• /
• pp.91-112
• /
• 2009

The bullwhip effect means the phenomenon of increasing demand variation as moving UP to the upstream in the supply chain. Therefore, it is recognized that the bullwhip effect is problematic for effective supply chain operations. In this paper, we exactly quantifies the bullwhip effect for the case of stochastic lead time and seasonal demand in two-echelon supply chain where retailer employs a base-stock policy considering SARMA demand processes and stochastic lead time. We also investigate the behavior of the proposed measurement for the bullwhip effect with autoregressive and moving average coefficient, stochastic lead time, and seasonal factor.

• 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.

• 한국시뮬레이션학회:학술대회논문집
• /
• 한국시뮬레이션학회 2003년도 춘계학술대회논문집
• /
• pp.129-134
• /
• 2003

In this paper, we determine optimal reduction in the lead time and setup cost for some stochastic inventory models. And we propose more general model that allow the backorder rate as a control variable. We first assume that the lead time demand follows a normal distribution. And we assume that the backorder rate is dependent on the length of lead time through the amount of shortages. The stochastic models analyzed in this paper are the classical continuous and periodic review policy models with a mixture of backorders and lost sales. For each of these models, we provide a sufficient conditions for the uniqueness of the optimal operating policy. We also develop algorithms for solving these models and provide illustrative numerical examples.

• 한국국방경영분석학회지
• /
• 제18권2호
• /
• pp.181-191
• /
• 1992

In this paper in order to prevent break of operation of equipments resulted from the delay of parts supply, the continuous review(Q, r) inventory model with probabilistic lead time is developed. If the lead tire is random varivable, the cycle also is stochastic. Then it is not easy to obtain the total cost equation of this inventory model. Therefore it is assumed that one cycle is the interval of reorder points. When the lead time is assumed to have exponential probability distribution, the lot-size and reorder point which minimize total cost are obtained. And as the lead time increases, the order quantity and the total cost are greater, but the reorder point increases by a certain point of time and then decreases.

• 대한산업공학회지
• /
• 제31권1호
• /
• pp.27-35
• /
• 2005

Due to the importance of lead time demand in the design of inventory management systems, researchers and practitioners have paid continuous attention and a few analytic models using the compound distribution approach have been reported. However, since the nature of compound distributions is hardly amenable, the analytic models have been done by non‐recognition of the compound nature of some components to reduce the analytic task. This study concerns some of the important aspects in the analytic models. Through the theoretic examination of the analytic model approach and the comparison with the rigid compound stochastic process approach, this study clarifies the assumptions implicitly made by the analytic models and provides some precautions in using the analytic models. Illustrative examples are also presented.

• 대한산업공학회지
• /
• 제2권1호
• /
• pp.79-83
• /
• 1976

This paper deals with a computer simulation for the stochastic inventory system in which the decision rules are associated with the problem of forecasting uncertain demand, lead time, and amount of shortages. The model consists of mainly three parts; part I$\cdots$the model calculates the expected demand during lead time through the built-in subrou tine program for random number generator and the probability distribution of the demand, part II$\cdots$the model calculates all the possible expected shortages per lead time period, part III$\cdots$finally the model calculates all the possible total inventory cost over the simulation period. These total inventory costs are compared for searching the optimal inventory cost with the best ordering quantity and reorder point. An application example of the simulation program is given.

• 대한교통학회지
• /
• 제10권3호
• /
• pp.7-20
• /
• 1992

The common cycle time for the linded signals is usually determined for the critical intersecion, just because the cpacity of a signalized intersection depends on the cycle time. This may not be optimal since the interactions between the flow and the spatial structure of the route or the area are disregarded in this case. It is common to separate the total delay incurred at signals into two parts, a deterministic or uniform delay and a stochastic or random delay. The deterministic delays and the stochastic delays on the artery particularly related to signal cycle time. For this purpose a microscopic simulation technique is used to evaluate deterministic delays, and a macroscopic simulation technique based on the principles of Markov chains is used to evaluate stochastic delays with over flow queue. As a result of investigating the relations between deterministic delays and cycle time in the various circumstances of spacing of signals and traffic volume. As for stochastic delays the resalts of comparisons of the macroscopic simulation and Newell's approximation with the microscopic simulation indicate that the former is valid for the degree of saturation less than 0.95 and the latter is for that above 0.95. Newell's argument that the total stochastic delay on an arterial is dominated by that at or caused by critical intersection is certified by the simulation experiments. The comprehensive analyses of the values of optimal cycle time with various conditions lead to a model. The cycle time determined by this model shows to be approximately 70% of that calculated by Webster's.

• 대한산업공학회지
• /
• 제5권1호
• /
• pp.59-66
• /
• 1979

The objective of this paper is to develop a stochastic inventory system model under the so-called continuous-review policy with a Poisson one-at-a-time demand process, iid customer inter-arrival times {Xi}, backorders allowed, and constant procurement lead time $\gamma$. The distributions of the so-called inventory position process {$IP_{(t-r)}$} and lead time demand process {$D_{(t-r,t)}$} are formulated in terms of cumulative demand by time t, {$N_t$}. Then, for the long-run expected average annual inventory cost expression, the "ensemble" average is estimated, where the cost variations for stock ordering, holding and backorders are considered stationary.

• 대한안전경영과학회지
• /
• 제15권1호
• /
• pp.217-229
• /
• 2013

As customers' demands for diversified small-quantity products have been increased, there have been great efforts for a firm to respond to customers' demands flexibly and minimize the cost of inventory at the same time. To achieve that goal, in SCM perspective, many firms have tried to control the inventory efficiently. We present an mathematical model to determine the near optimal (s, S) policy of the supply chain, composed of multi suppliers, a warehouse and multi retailers. (s, S) policy is to order the quantity up to target inventory level when inventory level falls below the reorder point. But it is difficult to analyze inventory level because it is varied with stochastic demand of customers. To reflect stochastic demand of customers in our model, we do the analyses in the following order. First, the analysis of inventory in retailers is done at the mathematical model that we present. Then, the analysis of demand pattern in a warehouse is performed as the inventory of a warehouse is much effected by retailers' order. After that, the analysis of inventory in a warehouse is followed. Finally, the integrated mathematical model is presented. It is not easy to get the solution of the mathematical model, because it includes many stochastic factors. Thus, we get the solutions after the stochastic demand is approximated, then they are verified by the simulations.

• Management Science and Financial Engineering
• /
• 제15권1호
• /
• pp.33-49
• /
• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.