• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.121-132
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• 2022

The uncertainty regarding inventory may impart dynamic impacts on corporate-level financial decisions. Among others, a decision about capital investment is a crucial decision that requires overall financial stability. Following these theoretical notions, the current study aims to identify possible consequences of inventory volatility relating to corporate capital investment decisions. We employed ten years of data (2010-2019) of non-financial sector firms to achieve the objective. The Driscoll-Kraay model was used to quantify the regression. The statistical results imply that inventory volatility negatively influences capital investment decisions due to information asymmetry about the current financial position. Additionally, more volatility brings discrepancies in managers' investing decisions to fulfill the possible demand options of capital investment that require processing the inventory. However, based upon the statistical findings, it is suggested to corporate managers that they should consider the financial sensitivity of enterprises regarding inventory volatility. Thus, the current study introduces new thoughts regarding inventory volatility and its empirical role in determining capital investment.

• Journal of the military operations research society of Korea
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• v.3 no.2
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• pp.79-89
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• 1977

The purpose of this thesis is to overcome the shortcomings of the existing system which lacks cost-conciousness and does not consider the essentiality or the importance of an item, and to seek the method of providing effective, efficient and economic supply which is the objective of the military inventory management. Selective management technique and lot size model whose demand, and order and shipping time are distributed, are intorduced, and required distributions and parameters are analyzed. Finally hypothetical data are utilized to obtain the model output, which are compared with the existing model and analyzed.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.27-36
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• 1990

This study deals with the dynamic transportation-inventory model for a single product from which the optimal procurement quantities and the transportation modes are determined simultaneously over a finite planning horizon. Moreover, it covers the situation where quantity discounts are applied to the transportation cost as well as the purchase cost and disposals of the excess are possible at the end of each period. For a relevant mathematical model formulated, the theorems and properties of an optimal solution are discussed to present the efficient algorithm. A numerical example is solved to illustrate the algorithm developed.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.49-59
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• 2011

A ship scheduling model is presented for the raw material transportation problem with yard storage constraints in a steel mill. The problem is formulated as 0, 1 mixed integer programming considering such constraints as loading port conditions, ship size and hold capacity, unloading conditions, and yard storage space. In addition, inventory related constraints including safety stock are taken into consideration to support the continuous operations of steel making process. The proposed model has been implemented and applied successfully to a real world problem, and its results show the improvement of performance compared to the traditional method. For example, the arrival dates of ships are determined satisfying the constraints. The total inventory level is minimized at the stock yard as a result. Also, the safety inventory level is always kept at the planning stage, and the standard deviation of total inventory level is reduced significantly. Further research is expected to develop efficient heuristics to have a better response time for even larger scale problems.

• Nuclear Engineering and Technology
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• v.21 no.4
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• pp.308-320
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• 1989

The objective of this work is to investigate the effects of diminished primary coolant inventory and the presence of noncondensible gas during single- and two-phase natural circulation in a PWR loop model. The test model was composed of two loops with a U-tube heat exchanger in each loop. Through a series of tests, it has been confirmed that the two-phase natural circulation flow rates were greatly dependent on primary coolant inventory as previous investigators observed. The primary coolant inventory limit to maintain two-phase natural circulation was found to be the amount of the coolant necessary to keep the waterline of the coolant nozzle hole center in this model. The presence of noncondensible gas impede the single-phase natural circulation, but it did not affect the two-phase natural circulation significantly.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.563-568
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• 2013

The purpose of this study is to find the analytic solution for determining the optimal capacity (lot-size) of a batch-storage network to meet the finished product demand under infrequent shutdowns. Batch processes are bound to experience random but infrequent operating time losses. Two common remedies for these failures are duplicating another process or increasing the process and storage capacity, both of which are very costly in modern manufacturing systems. An optimization model minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units is pursued with the framework of a batch-storage network of which flows are susceptible to infrequent shutdowns. The superstructure of the plant consists of a network of serially and/or parallel interlinked batch processes and storage units. The processes transform a set of feedstock materials into another set of products with constant conversion factors.A novel production and inventory analysis method, the PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model stems from the fact it provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance a proper and quick investment decision at the early plant design stagewhen confronted with diverse economic situations.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.6
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• pp.1546-1555
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• 2015

This study was performed to analyze the item characteristics of competency inventory for designer (CID), which Gil (2011) developed for measurement of design competency. To accomplish the purpose of this study, general partial credit (GPC) model based on polytomous item response theory was applied. The findings were as follows: First, CID is a reliable instrument for measuring design competency. Second, most items of CID have low item discrimination and average item difficulty according to the GPC model. Especially, there are some problems to have low item discrimination in view of validation. To improve the goodness of CID, we will need to examine why CID has low item discrimination.

• IE interfaces
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• v.21 no.4
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• pp.444-455
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• 2008

In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.51-58
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• 1991

This paper presents a single-echelon, single item, stochastic lead time and static demand 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. In this situations, an objective function representing the average annual cost of inventory system is obtained by defining a time-proportional backorder cost and a fixed penalty cost per unit lost. The optimal operating policy variables minimizing the average annual cost are calculated iteratively. At the extremet ${\beta}=1$, the model presented reduces to the usual backorder case. A numerical example is solved to illustrate the algorithm developed.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.44-51
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• 2017

In today's competitive environment, supply chain management is a major concern for a company. Two of the key issues in supply chain management are transportation and inventory management. To achieve significant savings, companies should integrate these two issues instead of treating them separately. In this paper we develop a framework for modeling stochastic programming in a supply chain that is subject to demand uncertainty. With reasonable assumptions, two stochastic programming models are presented, respectively, including a single-period and a multi-period situations. Our assumptions allow us to capture the stochastic nature of the problem and translate it into a deterministic model. And then, based on the genetic algorithm and stochastic simulation, a solution method is developed to solve the model. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.