• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.349-357
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• 2002

This research is basically deals with an inventory distribution system with several regional sales branches. Under the continuous review policy, each sales branch places an order to its supplier whenever on hand plus on order inventory falls on the order point, and the order quantity is received after elapsing a certain lead time. This research first shows the method how to apply the product with low lever of demand into the continuous review policy. For the application, we use an order level as the maximum level of inventory during an order cycle. Also we analyze the lost sales case as a customer behavior. Further we use variable demands and variable lead times for more realistic situation. Based on the above circumstances, the research mainly discusses those methods to decide the optimal order level, order point, and order quantity for each sales branch which guarantees the system wide goal level of service, while keeping the minimum level of the system wide total inventory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.8-13
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• 2015

One of the most usual indicators to measure the performance of any inventory policy is the mean physical stock. In general, when estimating the mean physical stock in periodic review inventory systems, approximate approaches are often utilized by practitioners and researchers. The mean physical stock is generally calculated by a simple approximation. Still these simple methods are frequently used to analyze various single stockpoint and multi-echelon inventory systems. However, such a simple approximation can be very inaccurate. This is particularly true for low service levels. Even though exact methods to calculate the mean physical stock have been derived, they are available for specific cases only and computationally not very efficient, and therefore less useful in practice. In literature, approximate approaches, such as the simple, the linear, and Simpson approximations, were derived for the periodic review inventory systems that allow backorders. This paper modifies the approximate approaches for the lost sales case and evaluates the modified approximate approaches. Through computational experiments, average (and maximum) percentage deviations of mean physical stock between the exact method and the modified approximations are compared in the periodic review inventory system with lost sales. The same comparison between the modified and the original approximations are also conducted, in order to examine the performance of modified approximations. The results show that all modified approximations perform well for high service levels, but also that the performance may deteriorate fast with decreasing service level. The modified Simpson approximation is clearly better. In addition, the comparison between the modified and the original approximations in the periodic review inventory system with lost sales shows that the modified approximation outperforms the original approximation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.3
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• pp.78-84
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• 2002

This research is basically deals with an inventory distribution system with several regional sides branches. Under the continuous review policy, each sales branch places an order to its supplier whenever on hand plus on order inventory falls on the order point, and the order quantity is received after elapsing a certain lead time. This research first shows the method how to apply the product with low lever of demand into the continuous review policy. For the application, we use an order level as the maximum level of inventory during an order cycle. Also we analyze the lost sales case as a customer behavior. Further we use variable demands and variable lead times for more realistic situation. Based on the above circumstances, the research mainly discusses those methods to decide the optimal order level, order point, and order quantity for each sales branch which guarantees the system wide goal level of service, while keeping the minimum level of the system wide total inventory.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.69-74
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• 1983

This article presents a deterministic inventory model for situations in which, during the stockout period, a fraction ${\beta}$ of the demand is backordered and the remaining fraction $1-{\beta}$ is lost. By defining a time proportional backorder cost and a fixed penalty cost per unit lost, a convex objective function representing the average annual cost of operating the inventory system is obtained. The optimal operating policy variables are calculated directly. At the extremes ${\beta}\;=\;1$ and ${\beta}\;=\;0$ the model presented reduces to the usual backorders and lost sales case, respectively.

• The Journal of Information Systems
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• v.30 no.2
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• pp.105-126
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• 2021

Purpose The purpose of this study is to implement a optimal machine learning model about the cancellation prediction performance in car sales business. It is to apply the data set of accumulated contract, cancellation, and sales information in sales support system(SFA) which is commonly used for sales, customers and inventory management by imported car dealers, to several machine learning models and predict performance of cancellation. Design/methodology/approach This study extracts 29,073 contracts, cancellations, and sales data from 2015 to 2020 accumulated in the sales support system(SFA) for imported car dealers and uses the analysis program Python Jupiter notebook in order to perform data pre-processing, verification, and modeling that is applying and learning to Machine learning model after then the final result was predicted using new data. Findings This study confirmed that cancellation prediction is possible by applying car purchase contract information to machine learning models. It proved the possibility of developing and utilizing a generalized predictive model by using data of imported car sales system with machine learning technology. It can reduce and prevent the sales failure as caring the potential lost customer intensively and it lead to increase sales revenue by predicting the cancellation possibility of individual customers.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.127-136
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• 1998

This paper presents a stochastic partial backorder inventory model for the situation in which demand follows normal distribution and back order ratio during that stockout period decreases exponentially according to the length of backorder period. In the paper, an objective function is formulated to minimize the average annual cost, which is the sum of the ordering, carrying, time-proportional backordering, and lost sales cost. And then sensitivity analysis for various exponential backorder ratios and standard deviations of leadtime demand are presented. The inventory model in the paper is reduced to a backorder model and lost sales model, when backorder ratio is 1 and 0, respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.8-13
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• 2003

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives In a stationary Poisson process The problem Is formulated using METRIC-approximation in a combined approach of pricing and (S-1.S) Inventory policy, for which an iterative solution algorithm is derived with respect to the corresponding one-warehouse multi-retailor supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed The computational results show that the proposed algorithm is efficient and derives quite good decisions

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.48-54
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• 2010

S plastic injection molding factory located at Namdong Industrial Complex in Incheon produces plastic parts for semiconductor, vacuum cleaners, office furniture, etc. It produces the parts to customers' order and delivers them directly to customers at due dates using the trucks of freight company. In recent years, it has been suffered from the excessive production cost, high lost sales rate, rigid response to customers' order, and high delivery cost, which affect negatively on its profit. This paper introduces a case study on the profit increase through a newly proposed production and distribution method which applies a make-to-stock and multi-visit delivery strategy at S plastic injection molding factory. The proposed method is evaluated by comparing with the current method with respect to sales profit using the historical data of customer demand. It is confirmed through the computational experiments that the proposed production and distribution method yields almost double increase in profit resulted from the increased production, reduced lost sales, reduced production cost, and reduced delivery cost.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.73-73
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• 1994

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.61-69
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• 2019

The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.