• 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.

• Korean Management Science Review
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• v.30 no.3
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• pp.17-31
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• 2013

The purpose of this paper is to illustrate the importance of identifying and considering 'purchase dependence' when purchase of an item is dependent on availability of other items demanded in the same order. This paper is the first study to develop an inventory model for purchase-dependent inventory systems. Through simulation experiments, we demonstrate that the developed inventory model incurs less inventory operations cost than other inventory models that ignore purchase dependence. For empirical validation of the developed inventory model, the actual inventory data at the Hyundai Engine Europe Service Center is used. We explain the process of identifying purchase dependencies among items through a data mining technique. The empirical study results in similar results to the simulation experiment, demonstrating that the developed inventory model is applicable to real situations.

• The Journal of Fisheries Business Administration
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• v.21 no.2
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• pp.55-84
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• 1990

The objective of this study is to develop an inventory model for the inventory management of a stocking point which sells processed fisheries products. The study, first of all, sets up fisheries processing companies, food companies, apparel companies, pharmaceutical companies and electronic and electrical companies as a population. Then, a comparative study is empirically applied to obtain the inventory characteristics of final products by industry through a survey of a sample selected by a random sampling procedure. The major inventory characteristics of processed fisheries products obtained from the above analysis can be summarized as follows : 1) The major demand characteristics of processed fisheries products is to have wide seasonal fluctuations because the supply of raw materials (i.e., fisheries products) heavily depends on the productive capacity of nature. 2) It has found that fisheries processing companies are the worst in inventory management among the various industries selected in the sample. However, the self-rating of inventory management system by inventory managers of companies shows that the fisheries processing companies are relatively higher than the other companies. 3) The portion of inventory holding cost out of inventory relevant cost is very high for processed fisheries products compared with final products of the other industries. 4) Processed fisheries products are distributed to final consumers through roughly two distribution echelons and take a parallel type inventory system for their distribution structure. In order to develop an inventory model which reflects the inventory characteristics of processed fisheries products mentioned in the above, an inventory model with partial backorders is developed under the situation of stochastic lead time under the consideration of the inventory characteristics of processed fisheries products and then an iterative solution method is provided for the model. Then this study analyzes sensitivity for the standard deviation of lead time in the model by numerical examples.

• Industrial Engineering and Management Systems
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• v.8 no.2
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• pp.72-79
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• 2009

The ultimate goal of inventory management is to decide the timing and the quantity of ordering in response to uncertain demands. Recently, some researchers have focused upon an impact of distortions in the information, e.g., customer order cancellation, on an economical inventory policy. The customer order cancellation is considered a kind of distortions in demands, because a demand that is eventually cancelled is equivalent to a phony demand. Also, there are some additional distortions in the inventory information. For instance, the procurement of suppliers may include some nonconforming items as a result of imperfect production and inspection by the suppliers, and/or damage in transit. The nonconforming item should be considered a kind of distortions in the inventory information, because the nonconforming item is equivalent to a phony stock. In this article, we consider an inventory model under the situation that customers can cancel their orders and the procurement of suppliers may include some nonconforming items. Then, we introduce the customer order reservation into the inventory model for the purpose of avoiding the costly backlogs, because the customer order reservation gives retailers a period to fulfill customer's requests. We formulate a periodic review (s, S) inventory model and investigate the economical operation under the situation mentioned above. Further, through the sensitivity analysis, we show the impact of these distortions and the effect of the customer order reservation on the inventory policy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.201-204
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• 1997

This study is focussed on optimization problems which require allocating the restricted inventory to demand points and assignment of vehicles to routes in order to deliver goods for demand sites with optimal decision. This study investigated an integrated model using three step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations. we developed several sub-models such as; first, an inventory-allocation model, second a vehicle-routing model based on clustering and a heuristic algorithms, and last a vehicle routing scheduling model, a TSP-solver, based on genetic algorithm. Also, for each sub-models we have developed computer programs and by a sample run it was known that the proposed model to be a very acceptable model for the inventory-allocation and vehicle routing problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.53-56
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• 1996

The conventional inventory models are concerned with the items of which utilities and amount of numbers are constant over time. But in practice the items in inventory systems are increasing or decreasing. This study is concerned with the development of ameliorating inventory models. The ameliorating inventory is the inventory of goods whose utility increases over the time by ameliorating activation. The term ameliorating inventory is used in this paper at least, since the terminology is not standard well known. This study is performed according to areas; one is an economic order quantity(EOQ) model for the items whose utility is ameliorating in accordance with Weibull distribution, and the other is a partial selling quantity(PSQ) model developed for selling surplus inventory accumulated by ameliorating activation. Computer programs are developed to obtain the optimal ordering and selling quantity. Numerical examples to illustrate the effect of ameliorating rate on inventory polices are shown at the end of this paper.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.742-749
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• 2002

This paper deals with a continuous-review two-echelon inventory model with one-for-one replenishment and Poisson demand where transshipments among retailers are allowed. Two classes of inventory systems are considered by the number of distribution centers(DCs) which provide each retailor with inventory items. 1:N class inventory system and M:N class inventory system respectively. Two-phase model is constructed to find out the optimal inventory positions which minimize supply chain costs. Approximations for customer service levels of the system are evaluated in the first phase, and the optimal inventory positions are found subject to the constraints for service level in the second phase. Simulation tests are performed to assure the effectiveness of the proposed model. The effect of transshipment is evaluated.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.95-115
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• 2013

In traditional inventory models, purchase prices of raw materials are assumed to be fixed and have no effect on the optimal choice of inventory policies. However, when purchase prices fluctuate continuously over time, inventory costs are heavily affected by purchasing prices. Risk-averse inventory model decides order quantity and ordering time by considering not just purchase prices but also the risk from the discrepancy between estimated prices and realized prices. In this paper, we propose a myopic inventory policy which incorporates price risk into deciding ordering time and quantities. While the existing risk-averse model has no mechanism to reallocate inventories already purchased for a specific future period, the revised one reallocates initial inventories of each period to other future periods so that it can avoid purchasing raw materials at high prices. Experimental results demonstrate that the revised model outperforms the existing one in respect of total cost and variability.

• The Journal of Information Systems
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• v.6 no.1
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• pp.223-256
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• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.