• 한국국방경영분석학회지
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• 제5권2호
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• pp.39-54
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• 1979

• International Journal of Advanced Culture Technology
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• 제8권3호
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• pp.300-306
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• 2020

This study analyzes the distributor's inventory model in a two-stage supply chain consisting of the supplier, the distributor and the end customer. The supplier will allow a credit period before the distributor settles the account with him in order to stimulate the demand for the product he produces. It is also assumed that the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. As a result, the availability of a credit transaction leads to an increase in inventory levels. On the other hand, in the case of deteriorating products in which the utility of the product perish over time, the deterioration rate with time plays a role in reducing inventory levels. In this regard, we analyze the effect of the length of the credit period and the degree of product deterioration on the distributor's inventory level. For the analysis, we formulate the distributor's annual net profit and analyze the effect of the length of credit period and deterioration rate of the product on inventory policy numerically.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2002년도 추계학술대회 논문집
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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.

• 품질경영학회지
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• 제16권1호
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• pp.78-87
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• 1988

The purpose of this study is to develop the algorithm applicable to the integrated production inventory model under quantity discount. To achieve this purpose, the integrated production inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system is considered. The product is manufactured in batches and the raw materials are obtained from outside suppliers but some of the raw materials are discounted according to the purchasing quantity. The intergrated production inventory problem considered in this study is formulated by the non-linear mixed integer programming model, and the optimal solution is obtained by using the algorithm developed by Goyal. Then, the algorithm developed by this study is applied to the quantity discount problem, and the optimal solution is revised by this results. The quantity discount algorithm of the integrated production inventory model developed by this study gives a systematic procedure to obtain the optimum policy to minimize the total cost in any case. The numerical example involving 20 raw materials and 5 raw materials among them are discounted according to the purchasing quantity is given to verify the mathematical model and the algorithm developed in this study.

• 한국경영과학회지
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• 제30권2호
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• pp.117-129
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• 2005

This paper considers a make-to-order inventory-production system in which customer orders are admitted only when the number of outstanding customer orders is below a value committed by the system. We deal with general distributions for the customer order Inter-arrival, production, and replenishment lead time processes. Monotonicities of the optimal average cost with respect to these distribution parameters are established using sample path coupling arguments. When distributions are given as an exponential one, we implement a sensitivity analysis on the optimal inventory policy and show that it has monotonicities with respect to system costs using dynamic programming.

• Management Science and Financial Engineering
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• 제16권3호
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• pp.1-20
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• 2010

In this paper, the impact of various system parameters such as the parameters of actual demand process, the review periods and the lead times, under each combination of inventory policies and information sharing, on the long run average inventory cost per period incurred at each participant in a supply chain, is considered. For this purpose, numerical studies are conducted, from which some valuable information as to how sensitive our long run average inventory cost per period are as the model parameters change is gleaned, from which, in turn, some managerial insights are gleaned in order for industry practitioners to perform better in supply chain management.

• 대한산업공학회지
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• 제5권1호
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• pp.59-66
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• 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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.391-402
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• 2006

Most previous studies considering inventory models for imperfect quality assumed that defective items could be completely detected by inspection and fixed before delivery to customers. This makes it difficult to adopt their research results to practice. This study reduces the assumption of perfect inspection, and presents an inventory model considering reverse logistics caused by imperfect inspection. System dynamics model is used to describe complex and dynamic problem and to show the effect of imperfect inspection on profit by simulation. Then, this article provides a guideline for the inspection policy which provides the maximum profit.

• 산업경영시스템학회지
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• 제38권2호
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• pp.145-151
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• 2015

As order quantity is increased, the ordering cost per item will be cheaper due to saving of transportation and material handling costs. In this paper, two realistic assumptions such as quantity discount and budget limit are considered. Quantity discount means that all units in the order will be discounted according to the predetermined order levels. Budget limit represents that the costs for inventory investments are bounded. This paper develops a Lagrangian relaxation approach for a continuous review inventory model with a budget constraint and quantity discounts. Computational results indicate that the proposed approach provides a good solution. Sensitivity analysis is done to get some insights on budget limit and quantity discount. As budget limit or the amount of discount according to order quantity is increased, order quantity is increased, whereas reorder point is not always increased.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 춘계학술대회
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.