• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.260-263
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• 2003

This paper has developed the computer integration manufacturing system and Internet based tele-operations. The functions of CIMS include production planing, material requirement planning, work order generation, process control, quality control, shipping planning, warehouse and inventory management and material cost accounting.[1] In this paper focuses on the automatic warehouse control and inventory management by developing the information system as well as the Internet-based integration. The system overview is divided into three parts, the mechanical system, the computer and developed software to control and manage the information and the communication system. The mechanical system consists of the warehouse machine and forklift mobile robot controlled by programmable logic controller (PLC). The computer works on many functions such as control station interfaces with PLC, managing database and inventory, and Internet server to broadcast the inventory database to users via World Wide Web and monitoring the operation on web camera. Our scheme the inventory database can be checked easily anywhere and anytime when the users connect to the Internet. In this article, the lead-time and inventory level can be reduced therefore the holding cost and operating time is also decreased.

• Korean Management Science Review
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• v.31 no.2
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• pp.1-13
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• 2014

In almost all of the organizations, the cost for acquiring and maintaining the inventory takes a considerable portion of the management budget, and thus a certain constraint is set upon the budget itself. The previous studies on inventory control for each item that aimed to improve the fill rate, backorder, and the expenditure on inventory are fitting for the commercially-operated SCM, but show some discrepancies when they are applied to the spare parts for repairing disabled systems. Therefore, many studies on systematic approach concept considering spare parts of various kinds simultaneously have been conducted to achieve effective performance for the inventory control at a lower cost, and primarily, METRIC series models can be named. However, the past studies were limited when dealing with the probability distributions for representing the situation on demand and transportation of the parts, with the (S-1, S) inventory control policy, and so on. To address these shortcomings, the Continuous Time Markov Chain (CTMC) model, which considers the phase-type distributions and the (s, Q) inventory control policies to best describe the real-world situations inclusively, is presented in this study. Additionally, by considering the cost versus the system availability, the optimization of the inventory level, based on this model, is also covered.

• IE interfaces
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• v.25 no.2
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• pp.163-169
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• 2012

This paper proposes an efficient portfolio management methodology named sSPPM with consideration of risk and required return. sSPPM employs Markowitz's portfolio model to select securities and adopts ($s$, $S$) policy that is a well-known technique in the inventory control area to revise the current portfolio. Computational experiments using virtual stock prices generated by monte carlo simulation method as well as real stock ones of KOSPI for recent 4 years are conducted to show the excellence of the portfolio management under ($s$, $S$) policy framework. The result shows that sSPPM is remarkably superior to both 6 or 12 months based periodic portfolio revision method and market (KOSPI index).

• Journal of Preventive Medicine and Public Health
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• v.21 no.1 s.23
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• pp.195-206
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• 1988

Two major issues of the blood bank management are quality assurance and inventory control. Recently, in Korea blood donation has gained popularity increasingly to allow considerable improvement of the quality assurance with respect to blood collection, transportation, storage, component preparation skills and hematological tests. Nevertheless the inventory control, the other issue of blood bank management, has been neglected so far. For the supply of blood by donation barely meets the demand, the blood bank policy on the inventory control has been 'the more the better.' The shortage itself by no means unnecessitate inventory control. In fact, in spite of shortage, no small amount of blood is outdated. The efficient blood inventory control makes it possible to economize the blood usage in the practice of state-of-the-art medical care. For the efficient blood inventory control in Korean hospitals, this tudy is to develop formulae forecasting the standard blood inventory level and suggest a set of policies improving the blood inventory control. For this study informations of $A^+$ whole bloods and packed cells inventory control were collected from a University Hospital and the Central Blood Bank of the Korean Red Cross. Using this informations, 1,461 daily blood inventory records were formulated.48 varieties of blood inventory control environment were identified on the basis of selected combinations of 4 inventory control variables-crossmatch, transfusion, inhospital donation and age of bloods from external supply. In order to decide the optimal blood inventory level for each environment, simulation models were designed to calculate the measures of performance of each environment. After the decision of 48 optimal blood inventory levels, stepwise multiple regression analysis was started where the independent variables were 4 inventory control variables and the dependent variable was optimal inventory level of each environment. Finally the standard blood inventory level decision rule was developed using the backward elimination procedure to select the best regression equation. And the effective alternatives of the issuing policy and crossmatch release period were suggested according to the measures of performance under the condition of the standard blood inventory level. The results of this study' were as follows ; 1. The formulae to calculate the standard blood inventory level($S^*$)was $S^*=2.8617X(d)^{0.9342}$ where d is the mean daily crossmatch(demand) for a blood type. 2. The measures of performace - outdate rate, average period of storage, mean age of transfused bloods, and mean daily available inventory level - were improved after maintenance of the standard inventory level in comparison with the present system. 3. Issuing policy of First In-First Out(FIFO) decreased the outdate rate, while Last In-First Out(LIFO) decreased the mean age of transfused bloods. The decrease of the crossmatch release period reduced the outdate rate and the mean age of transfused bloods.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1001-1005
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• 2004

The objective of this paper is to develop the flexible manufacturing system (FMS), which is cooperated with the automatic warehouse and inventory control under holonic manufacturing system (HMS). The HMS is a next wave of manufacturing revolution to deal with dynamic changing. The architecture of HMS is developed for cooperation system between the automatic warehouse agents and the manufacturing agents. This research applies the concept of HMS to develop a distributed control system for automatic warehouse and FMS by industrial network. The parts of prototype manufacturing agents consist of the conveyer system and 3-axises robot that provide the variety patterns in order to work as punch process. Each order of productions depends on the reorder points(RP) of inventory levels. The computation results indicate an improvement by comparing with traditional centralized control.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.217-229
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• 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.

• Journal of the Korea Society for Simulation
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• v.12 no.2
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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).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.904-913
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• 2005

This paper deals with an integrated problem of inventory control and dynamic pricing strategies for a commodity with price and sales-period dependent demand pattern, where a seller and customers have complete information of each other. The problem consists of two parts; one is each buyer's benefit problem which makes the best decision on price and time for buyer to purchase items, and the other one is a seller's profit problem which decides an optimal sales strategy concerned with inventory control and discount schedule. The seller's profit function consists of sales revenue and inventory holding cost functions. The two parts are closely related into each other with some related variables, so that any existing general solution methods can not be applied. Therefore, a simplified model with single seller and two customers in considered first, where demand for multiple units is allowed to each customer within a time limit. Therewith, the model is generalized for a n-customer-classes problem. To solve the proposed n-customer-set problem, a dynamic programming algorithm is derived. In the proposed dynamic programming algorithm, an intermediate profit function is used, which is computed in case of a fixed initial inventory level and then adjusted in searching for an optimal inventory level. This leads to an optimal sales strategy for a seller, which can derive an optimal decision on both an initial inventory level and a discount schedule, in $O(n^2)$ time. This result can be used for some extended problems with a small customer set and a short selling period, including sales strategy for department stores, Dutch auction for items with heavy holding cost, open tender of materials, quantity-limited sales, and cooperative buying in the on/off markets.