• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.99-103
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• 2008

An operational strategy for inventory control on finished goods in the distribution system has been given attention to many enterprises and many studies regarding this field have been done and is also on-going currently. It handling large scale of smallness type are so the requisition of customer which is various that over it continues more full scale merit. therefore, It is a tendency that many of enterprise is handling small scale of smallness type for environment change confrontation. but It is not easy for the enterprise to In customer demand diversification suiting because too need many cost. In addition, at enterprise charge extra weight because remainder inventory is causes of defective stock for a inefficient problem solution. this paper is rationalization of stock cost decrease for comparison evaluation of small scale quantity handling of singleness type and small scale quantity handling of largeness type.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.273-284
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• 2007

This paper studies a periodic review inventory model with an e-MarketPlace transaction in reconfigurable manufacturing system(RMS). A decision maker can expand/reduce production capacity/quantities and/or replenish/dispose inventories from/to e-MarketPlace urgently to satisfy the stochastic demands. If inventories are replenished or disposed through e-MarketPlace, this leadtime is shorter than the production leadtime, but unit purchasing or selling cost is more expensive than that of expanding capacity or reducing production quantities respectively. Henceforth, trade-off on these alternatives is considered. In addition to this, in order to consider the economy of scale, our model includes the fixed cost for purchasing from e-MarketPlace and capacity expansion. We use dynamic programming and K convexity methods to characterize the nature of the optimal policy. Finally, We present the optimal inventory control policy which is composed by the combinations of a base stock and (s,S) type policy.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.39-48
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• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.65-75
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• 2016

Unused spare parts of military equipments which have been kept in the warehouse for a long term have been recognized as wasting of defense budget which also decreased people's confidence in the field of national defence. It is known that overstock is caused by information distortion and bullwhip effect from downstream to upstream in the logistic support as is like business cases. After upgrading the logistic information system, it is possible for Army Logistics Command(ALC) to know demand information of end-user which is the key factor to reduce bullwhip effect. However, inventory is still overstocked and stock-out at the same time. Previous studies have not accounted for these phenomenons and have mainly focused on forecasting inventory level instead of budgetary process(budget period, PROLT, ASL/N-ASL). Thus, this study focuses on the information distortion, overstock and stock-out which caused by budgetary process in the logistic support with system dynamics and simulation.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• Journal of Environmental Science International
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• v.32 no.3
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• pp.181-189
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• 2023

In this study, sediment cores from unvegetated tidal flats in the Hampyeong Bay (west coastal wetland) and Dongdae Bay (south coastal wetland) were sampled, the blue carbon stock in the sediments was calculated, and the characteristics of the blue carbon stock were analyzed based on particle size of the sediments. The sediments in the Hampyeong Bay tidal flat had large particle size and low mud content, and the Dongdae bay tidal flat had small particle size and high mud content. The organic carbon content and blue carbon stock in the sediments were higher in the Dongdae tidal flat than in the Hampyeong Bay tidal flat. As a result of the regression function, in both the Hampyeong Bay and Dongdae Bay tidal flats, the sediments had the smaller particle size and higher mud contents the higher the organic carbon content and blue carbon stock. The sediments with smaller particle size had the larger specific surface area, so were feasible to adsorb and store more organic matters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.4
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• pp.125-138
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• 2006

This paper considers a periodic review, two-echelon inventory system with one central warehouse and several re-tailers facing normally distributed demand. The goal is to attain target fill rates, while the systemwide total holding costs are minimized. An important aspect of this problem is material rationing in the case of shortages. If a central warehouse has insufficient inventory to deliver all replenishment orders to retailers, all order quantities are should be adjusted according to some rationing rule. A simple but efficient rationing rule is proposed and compared with the Balanced Stock (BS) rationing as introduced by Heijden which is known to be the best rationing policy in the literature. Numerical results show that the proposed rationing rule is more cost effective than BS rationing, especially for the differences in holding costs between retailers are large.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.441-445
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• 2004

In this paper, we deal with an inventory model of a multi-stage, serial supply chain system where a single product type and nonstationary customer demand pattern are considered. The retailer and suppliers place their orders according to an echelon-stock based replenishment control policy. We assume that the suppliers can access online information on the demand history and use this information when making their replenishment decisions. Using a reinforcement learning technique, the inventory control parameters are designed to adaptively change as the customer demand pattern is altered, in order to maintain a given target service level. Through a simulation based experiment, we verified that our approach is good for maintaining the target service level.