• 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.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.198-208
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• 2007

Recently business enterprises have forced to face in fierce competition in today's global markets due to the short life cycles of products and the higher expectation of customers. Together with continuing advances in communications and transportation technologies, these environments have motivated the continuous evolution of the supply chain and the management techniques. This paper consider three-echelon inventory system which consist of one manufacturer, one distributor and N retailers for a single product under assumption of constant demand. This paper propose the inventory replenishment period using heuristic method and order policy through coordination of inventory replenishment period. The simulation results show that decrease the total cost of the three-echelon inventory system.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.63-78
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• 2004

This paper deals with a supplier-managed inventory(SMI) control for a two-echelon supply chain model with a service facility and a single supplier. The service facility is allocated to customers and provides a service using items of inventory that are purchased from the supplier, Assuming that the supplier knows the information of customer queue length as well as inventory position in the service facility at the time when it makes a replenishment decision, we identify an optimal replenishment policy which minimizes the total supply chain costs by reflecting these information into the replenishment decision. Numerical analysis demonstrates that the SMI strategy can be more cost-effective when the information of both customer queue length and inventory position is shared than when the information of inventory position only is shared.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.4
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• pp.33-53
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• 2010

When purchase prices of a raw material fluctuate over time, the total purchasing cost is mainly affected by reordering time. Existing researches focus on deciding the right time when the demand for each period is replenished at the lowest cost. However, the decision is based on expected future prices which usually turn out to include some error. This discrepancy between expected prices and actual prices deteriorates the performance of inventory models dealing with fluctuating purchase prices. In this paper, we propose a new inventory model which incorporates not only cost but also risk into making up a replenishment schedule to meet each period's demand. For each replenishment schedule, the risk is defined to be the variance of its total cost. By introducing the risk into the objective function, the variability of the total cost can be mitigated, and eventually more stable replenishment schedule will be obtained. According to experimental results from crude oil inventory management, the proposed model showed better performance over other models in respect of variability and cost.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.53-76
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• 2009

As the flourish of today's supply chain, the traditional model of replenishment will cause accumulation of excessive inventory to the retailers and customers, or cause shortages and inability to meet the demands. To solve this problem, Theory of Constraints (TOC) proposed the replenishment model of demand-pull, combined with the establishment of factory-ware-house to achieve performance improvement. In the absence of empirical research, this study applied the Bean Game developed by Dr. Goldratt to design a supply chain system for different scenarios, in order to allow players and managers better understanding and supporting the TOC replenishment method through the operations of the game.

• Journal of radiological science and technology
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• v.21 no.1
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• pp.35-39
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• 1998

We analyzed image factors to determine the characteristic factors that need for intelligent replenishment system of the auto film processor. We processed the serial 300 sheets of radiographic films of chest phantom without replenishment of developing and fixation replenisher. We took the digital data by using film digitizer which scaned the films and automatically summed up the pixel values of the films. We analyzed characteristic curves, average gradients and relative speeds of individual film using densitometer and step densitometry. We also evaluated the pH of developer, fixer, and washer fluid with digital pH meter. Fixer residual rate and washing effect were measured by densitometer using the reagent methods. There was no significant reduction of the digital density numbers of the serial films without replenishment of developer and fixer. The average gradients were gradually decreased by 0.02 and relative speeds were also gradually decreased by 6.96% relative to initial standard step-densitometric measurement. The pHs of developer and fixer were reflected the inactivation of each fluid. The fixer residual rates and washing effects after processing each 25 sheets of films were in the normal range. We suggest that the digital data are not reliable due to limitation of the hardware and software of the film digitizer. We conclude that average gradient and relative speed which mean the film's contrast and sensitivity respectively are reliable factors for determining the need for the replenishment of the auto film processor. We need more study of simpler equations and programming for more intelligent replenishment system of the auto film processor.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.329-333
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• 2003

This study presents supplier buyer models representing the interactions between supplier and buyer under a long-term replenishment contract in a supply chain system. We established the models according to the economic power of each party. Analysis based on Stackelberg game theoretic approach is tried for each model. We develop methods for each agent to follow to complete a contract for the best interest of each participant.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.334-337
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• 2003

In this paper we presents a centralized model for a long-term replenishment contract model in the supply chain system. We assume ARIMA demand process for reflecting more realistic demand data and present a solution which minimizes total system cost of the contract model between single supplier and buyer under centralized system. From the result of experiments we can observe that the proposed model generate better result than the decentralized model.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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• pp.195-206
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• 2006

본 연구는 제조자(공급자)와 중간분배자로 구성된 공급사슬에서 시간에 따라 일정률로 퇴화하는 퇴화성 제품을 다루는 중간분배자의 신뢰성있는 재고보충정책을 분석하였다. 문제 분석을 위하여 제조자는 고객의 수요를 증대시키기 위한 수단으로 중간분배자로부터의 제품대금에 대하여 일정기간 동안 신용거래를 허용한다는 가정과 함께 수송량에 따라 할인되는 수송비를 고려하여 모형을 수립하였고, 중간분배자의 경제적 재고보충정책을 결정하기 위한 해법을 개발하였다.