• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.53-62
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• 2009

Lee[15] examined quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model where quantity discounts are provided based on the previous order size. During the two periods, the retailer faces stochastic (truncated Poisson distributed) demands and he/she places orders to meet the demands. The manufacturer provides for the retailer a price discount for the second period order if its quantity exceeds the first period order quantity. In this paper we extend the above two-period model to a k-period one (where k < 2) and propose a stochastic nonlinear mixed binary integer program for it. In order to make the program tractable, the nonlinear term involving the sum of truncated Poisson cumulative probability function values over a certain range of demand is approximated by an i-interval piecewise linear function. With the value of i selected and fixed, the piecewise linear function is determined using an evolutionary algorithm where its fitness to the original nonlinear term is maximized. The resulting piecewise linear mixed binary integer program is then transformed to a mixed binary integer linear program. With the k-period model developed, we suggest a solution procedure of receding horizon control style to solve n-period (n < k) order decision problems. We implement Lee's two-period model and the proposed k-period model for the use in receding horizon control style to solve n-period order decision problems, and compare between the two models in terms of the pattern of order quantities and the total profits. Our computational study shows that the proposed model is superior to the two-period model with respect to the total profits, and that order quantities from the proposed model have higher fluctuations over periods.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.248-256
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• 2020

This study investigated whether the schema modes have validity in Korean adults. We examined the validity and reliability of the Schema Mode Inventory (SMI) in a Korean adult sample (N = 768; Mean age = 22.29 years; range = 19-55 years; 69.3% Males). Psychometric properties, such as factor structure, internal reliability, as well as intercorrelations among subscales were assessed. Confirmatory factor analyses yield satisfying fits for a 61-item Korean Schema Mode Inventory. Thirteen Schema Mode Inventory scales were found to have adequate reliability of the original 14 schema factors. Furthermore, the SMI scales differentiated between depressed and non-depressed participants as theoretically predicted. These findings imply that the SMI is a sound instrument to measure the schema mode model in a Korean setting for assessment prior to schema therapy.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.425-432
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• 2008

While the Vendor-Managed Inventory(VMI) is a convenient inventory replenishment policy for the customer company, the supplier usually bears the burden of higher inventory and urgent shipments to avoid shortage. Recently some manufacturers begin to fix the production schedule for the next few days (such as three days). Utilizing that information can improve the efficiency of the VMI. In this study, we present a myopic optimization model using a mixed inter programming; and a heuristics algorithm. We compare the performance of the two proposed methods with the existing (s, S) reorder policy. We consider the total cost as the sum of transportation cost and inventory cost at the customer's site. Numerical tests indicate that the two proposed methods significantly reduce the total cost over the (s, S) policy.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.131-138
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• 2014

Auto part industry supplies production for auto manufacturer and after market. These company have inventory for delivery. High inventory level can be good for delivery, but cost will be increase. Low inventory level can be customer unsatisfaction for delivery late. Low inventory level also is reason of low productivity by decreasing product batch size. These article suggest model for calculation a proper inventory level and prove a effect by simulation of some company.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.387-396
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• 1998

We consider the problem of determining the spare inventory level for a multiechelon repairable-item inventory system. Our model extends the previous results to the system which has an inventory at the central depot as well as at the several bases. We develop an algorithm to find spare inventory levels, which minimize the total expected cost and simultaneously satisfies a specified minimum service level. Comparisons of our algorithm with the simulation show that the algorithm is very accurate and efficient.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.1-19
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• 2002

This study shows the effect of inventory policy change from supplier-based to customer-based. We focus on the service level, cost, and information distortion of the Military Supply Chain(MSC) with System Dynamics. We design MSC model according to field practician interviews by using Vensim. The simulation makes a comparison between supply-based inventory policy performances and order-based inventory policy performances. In order to evaluate the MSC performances, we measure the accumulation of backlog(service level), supply chain cost, and order percentage overshoot(information distortion). The results show that 1) changing inventory policy from supplier-based to end customer order-based gets a good customer service, reduces MSC cost, and prevents information distortion, 2) changing inventory policy from supplier-based to immediate customer order-based reduces a small amount of MSC cost and deteriorates customer service, and 3) supply level is main factor for MSC performances improvement. This study implicates the policy change makes a improvement of MSC performance without introducing information system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.117-126
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• 2015

This paper is to analyze an integrated production and inventory model in a single-vendor multi-buyer supply chain. The vendor is defined as the manufacturer and the buyers as the retailers. The product that the manufacturer produces is supplied to the retailers with constant periodic time interval. The production rate of the manufacturer is constant for the time. The demand of the retailers is constant for the time. The cycle time of the vendor is defined as the elapsed time from the start of the production to the start of the next production, while the cycle times of the buyer as the elapsed time between the adjacent supply times from the vendor to the buyer. The cycle times of the vendor and the buyers that minimizes the total cost in a supply chain are analyzed. The cost factors are the production setup cost and the inventory holding cost of the manufacturer, the ordering cost and the inventory holding cost of the retailers. The cycle time of the vendor is investigated through the cycle time that satisfies economic production quantity with the production setup cost and the inventory holding cost of the manufacturer. An integrated production and inventory model is formulated, and an algorithm is developed. An numerical example is presented to explain the algorithm. The solution of the algorithm for the numerical examples is compared with that of genetic algorithm. Numerical example shows that the vendor and the buyers can save cost by integrated decision making.

• Nuclear Engineering and Technology
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• v.35 no.6
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• pp.515-522
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• 2003

Tritium behavior in the solid breeder blanket is one of the key factors in determining tritium self-sufficiency, as well as safety, of fusion reactors. Recently, a model has been developed to describe the tritium behavior in solid breeder material, which can predict the tritium release and inventory in the blanket. However, the model has limitation to account for tritium solubility effects, mainly existing as LiOT, especially inside the $Li_{2}O$ solid breeder. In order to improve the capability of predicting the LiOT precipitation in $Li_{2}O$ solid breeder, a new logic is developed and integrated in the existing tritium release and inventory calculation code. With the logic developed in this work, the code can have capabilities to analyze tritium release and inventories in $Li_{2}O$ under steady and transient conditions. It can be found that tritium inventory as LiOT is an important mechanism under pulsed operation, and the amount of inventory becomes higher as the tritium generation rate increases and the temperature decreases. Also, the temperature limits for the generation of LiOT precipitation are determined. Therefore the developed logic helps understand the tritium transport mechanism in $Li_{2}O$ solid breeder.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.109-115
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• 2023

This paper studied the problem of determining the optimal inventory level to meet the customer service target level in a situation where the customer demand for each branch of a nationwide retailer is uncertain. To this end, ISR (In-Stock Ratio) was defined as a key management indicator (KPI) that can be used from the perspective of a nationwide retailer such as Samsung, LG, or Apple that sells goods at branches nationwide. An optimization model was established to allow the retailer to minimize the total amount of inventory held at each branch while meeting the customer service target level defined as the average ISR. This paper proves that there is always an optimal solution in the model and expresses the optimal solution in a generalized form using the Karush-Kuhn-Tucker condition regardless of the shape of the probability distribution of customer demand. In addition, this paper studied the case where customer demand follows a specific probability distribution such as a normal distribution, and an expression representing the optimal inventory level for this case was derived.