• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.89-93
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• 2007

In this study, we consider an assembly line operated under a base-stock policy. A product consists of two parts, and a finished product transfers to a warehouse in which demands are satisfied. Assume that demands arrive according to a Poisson process and processing times at each production line are exponentially distributed. Whenever a demand arrives, it is satisfied immediately from an inventory in the warehouse if available; otherwise, it is backlogged and satisfied later by the next product exiting from production lines. In either case, an arriving demand automatically triggers the production of a part at both production lines. These two parts will be assembled into a product that eventually transfers to the warehouse. We obtain a closed form formula of approximation for delay time or lead time distribution of a demand when a base- stock level is s. Moreover, it can be applied to the optimal base-stock level which minimizes the total inventory cost. Numerical examples are presented to show our optimal base-stock level's quality.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.71-81
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• 2005

This Paper focuses on the effects of outside competition on an optimal echelon base stock level in a two stage supply chain. This is new in that we have been studying the effects of inside competition within a supply chain up to now. It is known that the optimal echelon base stock level with inside competition within a supply chain is less than the global optimal echelon base stock level without inside competition. This is due to the ' public goods ' nature of inventory. That is, more inventory is better, but one wants the other to invest more, thus resulting in under-investment. However, this phenomenon becomes weaker as outside competition increases. We show that as outside competition becomes stronger, the ' public goods ' effects decrease and the optimal echelon base stock level increases. If the level of competition is sufficiently high, the optimal echelon base stock level goes even higher than the global optimal echelon base stock level. We develop a theoretical model for the analysis and conduct a numerical analysis.

• KDI Journal of Economic Policy
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• v.40 no.2
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• pp.23-52
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• 2018

Given the limited availability of data in South Korea, this study proposes a method by which to estimate regional capital stock by modifying the benchmark year method (BYM) and applies it to estimate regional net capital stock by sector in transport infrastructure. First, it estimates time-varying sectoral depreciation rates using the sectoral net capital stock and the investment amount for each period. Second, it estimates the net capital stock of each period using the net capital stock in the base year and the investment in each period. Third, in order to ensure that the sum of net capital stocks by region is equal to the nationwide estimate, the national estimates are allocated to each region according to the proportion of the values derived from the previous stage. The proposed method can alleviate well-known problems associated with conventional BYMs, specifically the upward bias and arbitrary choice of the depreciation rate.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.93-104
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• 2007

We consider a supply chain where products are shipped to warehouse from manufacturing system to customers. Products are supplied from either in-house regular manufacturing or the secondary source such as subcontractor. The inventory in warehouse is controlled by base-stock policy, that is, whenever a demand arrives from customer, an order is released to the manufacturing system. Unsatisfied demand is backlogged. The manufacturing system is modeled as M/M/s+1/c queueing system, and the orders exceeding the given limit care blocked and lost. The steady state distribution of the outstanding orders and the throughput of the manufacturing system are functions of the level of engagement In the secondary source. There is a profit obtained from throughput and cost not only due to the engagement of the secondary source in the manufacturing system but also inventory positions. We want to maximize the total production profit minus the total cost of the production system by simultaneously determining the optimal level of engagement of the secondary source and the optimal base-stock level of the inventory. We develop two algorithms : one without guarantee of the optimal solution but with the small number of computations, the other optimal but with more computations.

• IE interfaces
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• v.22 no.4
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• pp.368-375
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• 2009

This paper considers a two-stage supply system consisting of two make-to-stock facilities. The facility in the first stage produces a single type of component in anticipation of future demands from the market and the end item production while the facility in the second stage produces the end item in anticipation of future demands from the OEM customers. The facility in the first stage has the option of to accept or reject each incoming demand from the market. In this paper, we address the problem of how to control the exogenous component demand and how to manage the production of the end item and the component so as to maximize the system's profit subject to the system costs. In this paper, we present a heuristic policy that is the base-stock production policy combined with a linear switching curve for component demand control. Numerical study is implemented under different operating conditions of the system and it shows that the performance of the heuristic is very promising compared to that of the optimal policy for the Markov model.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.323-330
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• 2014

Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.1-14
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• 2015

The purpose of this paper is to reveal two problems in the existing inventory systems in retail market, and to suggest a Two-Bin System under Automatic Ordering System considering only base-stock. Large retailers already have a sophisticated inventory system based on an automatic ordering principle. However, why does the out-of-stock (OOS) happen in large discount stores in spite of having a good inventory system? This paper suggests two systems after finding the root causes concerning the previous question. For evaluating the performance of each system, the random 200 data set in each sample group was generated from MINITAB 16 and obeyed the Poisson distribution. The existing inventory system in retail market cannot help generating OOS due to indwelling contradiction in itself. The reasons are the ordering deadline and the relationship between ordering quantity and base stock. This paper also demonstrates that these previous studies on inventory fall into the closed loop. Also the paper shows that the performance of the replenishment policy was better than traditional methods dealing with ordering quantity and base stock.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.115-123
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• 2006

The main focus of this study is to investigate the performance of a clark-scarf type multi-echelon serial supply chain operating with a base-stock policy and to optimize the inventory levels in the supply chains so as to minimize the systemwide total inventory cost, comprising holding and backorder costs as all the nodes in the supply chain. The source of supply of raw materials to the most upstream node, namely supplier, is assumed to have an infinite raw material availability. Retailer faces random customer demand, which is assumed to be stationary and normally distributed. If the demand exceeds on-hand inventory, the excess demand is backlogged. Using the echelon stock and demand quantile concepts and an efficient simulation technique, we derive near optimal inventory policy. Additionally we discuss the derived results through the extensive experiments for different supply chain settings.

• Analyses & Alternatives
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• v.2 no.2
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• pp.143-162
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• 2018

This paper focuses on the policy framework about "Quantitative and Qualitative Easing (QQE)" of Japan, and analyzes reasons why the policy goal was not reached. The QQE was introduced by the Bank of Japan in 2013 with the purpose of meeting the price stability target of 2% and getting out of deflation that prevents sustained price decline. However, despite the implementation of the bold monetary easing policy unprecedented in the world, the policy goal was not achieved as of June 2018. As a result of analyzing the causes, the following three structural factors were confirmed. 1) The rise in prices by QQE was limited because Japan's consumer price is strongly depending on import price. 2) The effect is high degree of uncertainty and limited because theoretical framework of reflationist which adopted QQE depends on "expectation formation" by "self-fulfilling expectation" and "multiple equilibria". 3) It was confirmed that the expansion of the monetary base did not lead to money stock due to the existence of Japanese liquidity trap, long-term low interest rate policy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.267-284
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• 2008

Consider a supply chain where products are produced at a manufacturing system, shipped to a distribution center, and then supplied to customers. The distribution center controls inventory based on a base-stock policy, and whenever a unit of product is demanded by a customer, an order is released to the production system. Unsatisfied demand is backordered, and the inventory and backordered units are a function of the base-stock level. The manufacturing system is modeled as an M/M/s/c queueing system, and orders exceeding the limited buffer capacity are blocked and lost. The throughput of the manufacturing system and the steady state distribution of the outstanding orders are functions of number of servers and buffers of the manufacturing system. There is a profit obtained from throughput and costs due to servers and buffers of the manufacturing system, and also costs due to inventory positions of the distribution center, and we want to maximize the total production profit minus the total cost of the supply chain by simultaneously determining the optimal number of servers and buffers of the manufacturing system and the optimal base-stock level of the distribution center. We develope two algorithms, one analytical but without guarantee of the optimal solution and one optimal but without complete analytical proofs. The problem integrates strategic problem of the manufacturing system with tactical problem of the distribution center in a supply chain.