• 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).

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.84-97
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• 2020

This paper aims to develop an optimized inventory management method for safety critical Instrument and Control (I&C) components. In this regard, the paper focuses on estimating the consumption rate of I&C components using demand forecasting methods. The target component for this paper is the Foxboro SPEC-200 controller. This component was chosen because it has highest consumption rate among the safety critical I&C components in Korean OPR-1000 NPPs. Three analytical methods were chosen in order to develop the demand forecasting methods; Poisson, Generalized Linear Model (GLM) and Bootstrapping. The results show that the GLM gives better accuracy than the other analytical methods. This is because the GLM considers the maintenance level of the component by discriminating between corrective and preventive.

• Journal of Korean Institute of Industrial Engineers
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• v.4 no.1
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• pp.49-55
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• 1978

This paper presents a new method, called a modified economic order quantity method, for determining the optimal inventory policy, which uses the rate of return as its decision criterion. Especially for the simplest possible inventory system with constant demand rate, no backlogging, no lead time, etc., the formula for the optimal order policy is derived. Also mentioned are the relative merits and shortcomings of this method compared to the conventional EOQ model.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.27-34
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• 2016

In this paper, we designed and implemented a system to easily check and manage book inventory using web and Android mobile device. In the previous conventional method, the user visits the bookstore directly and then checks the inventory. However, in this case, the user accessibility is inconvenient, and it is troublesome to check or reconfirm the inventory. In order to solve these inconveniences, we provide book inventory management system for requesting book purchase and inquiring bulletin board by book field, and then providing real time inventory check with book application and purchase functions. In addition, through the push notification function, we can catch up with the purchase status of the ordered books on the web and Android mobile device in real time. Therefore, we designed and implemented a function that enables bookstore operators and users to easily and conveniently manage by providing statistical information on inventory data.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.702-707
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• 2006

There have been certain extent of material inventory in construction site because of difficulties in ordering by small quantity, strategy of securing future requirements and prevention of delay. However, carrying these inventory entails a financial cost called inventory holding cost and decrease construction productivity, so proper inventory management in construction industry is important for construction efficiency and cost reduction. This study tries to find analytical method of inventory management. It includes ordering decision which decide how much to order and when to order. Setting these strategies including deciding safety inventory, input and ouput variability are able to controled.

• Industrial Engineering and Management Systems
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• v.8 no.2
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• pp.80-92
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• 2009

This paper addresses the inventory rationing issue embedded in the regional supply chain inventory replenishment problem (RSIRP). The concerned supply chain, which was fed by the national supply chain, consisted of a single warehouse distributing a single product to multiple stores (M-stores) with independent and normally distributed customer demand. It was assumed that the supply chain operated under the order-up-to level inventory replenishment system and had only one truck at the regional warehouse. The truck could make one replenishment trip to one store per period (a round trip per period). Based on current inventories and the vehicle constraint, the warehouse must make two decisions in each period: which store in the region to replenish and what was the replenishment quantity? The objective was to position inventories so as to minimize lost sales in the region. The warehouse inventory was replenished in every fixed-interval from a source outside the region, but the store inventory could be replenished daily. The truck destination (store) in each period was selected based on its maximum expected shortage. The replenishment quantity was then determined based on the predetermined order-up-to level system. In case of insufficient warehouse inventories to fulfill all projected store demands, an inventory rationing rule must be applied. In this paper, a new inventory rationing rule named Expected Cost Minimization (ECM) was proposed based on the practical purpose. The numerical results based on real data from a selective industry show that its performance was better and more robust than the current practice and other sharing rules in the existing literature.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.147-155
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• 2014

This paper suggests a specific model that could efficiently improve the interaction and the interface between WMS(Warehouse Management System) terminal and PDA terminal through real time processing in manufacturing shop. The proposed model shows that the new method can more efficiently perform to reduce processing time for shipping and receiving, compared with the current approach. As a result of the certain test among the main server, WMS system, and PDA terminal, it is noted in case of the new proposed system that the effects of proposed model are as follows: (a) While the receiving lead time for carrying by the current method was 2 hours, the receiving lead time by the new method was 20 minutes. (b) While the shipping lead time for carrying by the current method was 1 hours, the shipping lead time by the new method was 15 minutes. (c) While the inventory rate of accuracy by the current method was 85%, the inventory rate of accuracy by the new method was 98%.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.385-398
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• 2018

Although the importance of developing reliable and systematic GHG inventory has increased, the GIS/RS-based national scale LULUCF (Land Use, Land-Use Change and Forestry) sector analysis is insufficient in the context of the Paris Agreement. In this study, the change in $CO_2$ storage of forest land due to land use change is estimated using two GIS/RS methodologies, Sampling and Wall-to-Wall methods, from 2000 to 2010. Particularly, various imagery with sampling data and land cover maps are used for Sampling and Wall-to-Wall methods, respectively. This land use matrix of these methodologies and the national cadastral statistics are classified by six land-use categories (Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land). The difference of area between the result of Sampling methods and the cadastral statistics decreases as the sample plot distance decreases. However, the difference is not significant under a 2 km sample plot. In the 2000s, the Wall-to-Wall method showed similar results to sampling under a 2 km distance except for the Settlement category. With the Wall-to-Wall method, $CO_2$ storage is higher than that of the Sampling method. Accordingly, the Wall-to-Wall method would be more advantageous than the Sampling method in the presence of sufficient spatial data for GHG inventory assessment. These results can contribute to establish an annual report system of national greenhouse gas inventory in the LULUCF sector.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.1-10
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• 2015

In this paper, we consider multi-item inventory management. When managing a multi-item inventory, we coordinate replenishment orders of items supplied by the same supplier. The associated problem is called the joint replenishment problem (JRP). One often-used approach to the JRP is to apply a can-order policy. Under a can-order policy, some items are re-ordered when their inventory level drops to or below their re-order level, and any other item with an inventory level at or below its can-order level can be included in this order. In the present paper, we propose a method for finding the optimal parameter of a can-order policy, the can-order level, for each item in a lost-sales model. The main objectives in our model are minimizing the number of ordering, inventory, and shortage (i.e., lost-sales) respectively, compared with the conventional JRP, in which the objective is to minimize total cost. In order to solve this multi-objective optimization problem, we apply a genetic algorithm. In a numerical experiment using actual shipment data, we simulate the proposed model and compare the results with those of other methods.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.81-86
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• 2014

In this paper, a jointly optimal group replacement and spare provisioning policy is presented. Most maintenance policies assume that the spare inventory is always available, but in practice the maintenance schedule is affected by the availability of spare inventory. We present a maintenance-inventory model which jointly optimizes the group replacement interval and spare ordering quantity. Group replacement policy is used when a group of units are put in operation simultaneously. The operating fleet is replaced altogether at a predetermined number of units are failed. A sufficient level of spare inventory is carried to perform a number of group replacement. A cost rate expression which considers the group maintenance cost and inventory holding cost is derived and a heuristic method for searching the optimum value of decision variables is suggested. Numerical examples demonstrate the analytical results and the performance of the presented model.