• Journal of Korean Port Research
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• v.14 no.1
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• pp.37-45
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• 2000

Centralized safety stock in a periodic replenishment system which consists of one central warehouse and m regional warehouse can reduce backorders allocating the centralized safety stocks to regional warehouse in a certain instant of each replenishment cycle. If the central warehouse can not monitoring inventories in the regional warehouse, then we have to predetermine the instant of allocation according to demand distribution and this instant must be same for all different replenishment cycle. However, transition of inventory level in each cycle need not to be same, and therefore different instant of the allocation may results reduced shortage compare to the predetermined instant of allocation. In this research, we construct a dynamic model based on the assumption of monitoring inventories in the regional warehouse everyday, and develop an algorithm minimize shortage in each replenishment cycle using dynamic programming approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.1-9
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• 1987

This paper considers (S -1, S) inventory models which have wide applications in reparable spare parts inventory systems and multi-echelon systems. We assume a discrete compounds Poisson demand and order size dependent delivery times ; when the replenishment order size is n, we assume the delivery time distribution is arbitrary with finite mean $b_{n}$ . On the basis of the fact the outstanding orders follow a certain queueing process, we introduce the results of Fakinos (1982). We develop the efficient recursive formulae to find the optimal $S^{*}$ under several performance measures as a function of the decision variable S. The results of this paper can be applied to the multi-echelon systems such as MEETRIC.C.

• Journal of Distribution Science
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• v.14 no.9
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• pp.47-64
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• 2016

Purpose - This study reviews the past studies that have researched Vendor Managed Inventory (VMI) as a well-known supply chain collaboration program. The main goals of this study are to figure out how VMI brings significant benefits to the supply chain system and suggest additional areas that future studies would address to discover the true nature of VMI. Research design, data, methodology - This study conducts literature reviews on numerous studies that have researched VMI. The past studies are classified in terms of several main issues that have been commonly addressed by many researchers. This study also identifies three key collaborative features of VMI, which possibly explain why VMI improves the supply chain performance. Results - This study finds out that most past studies focused on a limited research issues about VMI. Many researchers have considered integrated decision making and information sharing to be key features that enables VMI to improve the supply chain performance. Conclusions - Based on the findings from the literature review, this study suggests that future studies on VMI take account of new research issues and pay attention to cost payment that researchers have rarely addressed.

• Journal of Korean Society for Quality Management
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• v.14 no.2
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• pp.21-27
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• 1986

This paper deals with a continuous review (s,S) spare part inventory system. The distributions of service life of each part and the replenishment lead time are assumed to be exponential. Assuming that there is never more than a single order outstanding, we obtain the average annual cost of operating the inventory system. If the length of stockout period is small enough to be neglected compared to the length of operating period, the optimal operating policy variables minimizing the cost rate can be calculated iteratively. For the case of one-for-one ordering (that is, s=S-1), an exact cost rate, and a closed form decision rule minimizing the cost rate are obtained for a more general situation in which more than one order is allowed to be outstanding and the distribution of the replenishment lead time is general.

• Korean Management Science Review
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• v.11 no.2
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• pp.99-131
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• 1994

This paper shows the direction in which logistics modellers should make their effort by examining the gap between desirable characteristics which logistics decision models should possess and deficiencies from which existing models suffer. For this purpose, we(1) categorized logistics models into facility planning, inventory management and transportation/delivery planning models, (2) carried out a wide survey of theoretical and industry models within each category and (3) assessed recent development of integrated logistics models.

• Korean Management Science Review
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• v.10 no.2
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• pp.79-91
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• 1993

Strategic decisions related to the design of a physical distribution system can be classified into three basic components : facility location, transportation, inventory decisions. In this research the interdependence of those decisions are expressed in a mathematical model such that the total relevant cost of the system is minimized. We suggested a heuristic technique for solving the model. In broad terms, our solution technique combines a heuristic method for determining which candidate DCs to open and an exact method for minimizing costs given a set of open DCs. And we also developed a decision supporting package for the design of a physical distribution system.

• Research in Community and Public Health Nursing
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• v.27 no.1
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• pp.43-50
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• 2016

Purpose: The purpose of this study was to investigate the relationship of depression and smartphone dependency with female college students' career decision-making self efficacy. Methods: This was a descriptive study. The survey participants were 497 female college students in M City and S City. Data were collected from November 16 to December 4, 2015 using self-report questionnaires including BDI (Beck Depression Inventory), Smartphone Dependency Scale, and CDMSES-SF (Career Decision-Making Self Efficacy Scale-Short Form). Data were analyzed through descriptive statistics, independent-samples t-test, ANOVA, and stepwise multiple regression. Results: Career decision-making self efficacy showed significant differences according to religion. Smartphone dependency was found to have a statistically significant negative correlation with career decision-making self efficacy and a positive correlation with depression. Depression was found to have a statistically significant negative correlation with career decision-making self efficacy. Stepwise multiple regression analysis revealed that the predictors of career decision-making self efficacy were depression (7.1%), religion (1.8%), and smartphone dependency (1.3%), accounting for a total of 10.6% of the variance. Conclusion: This study suggests that interventions to promote female college students' career decision-making self efficacy should consider their depression, religion, and smartphone dependency.

• Economic Analysis
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• v.24 no.3
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• pp.1-36
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• 2018

When it comes to explaining the relationship between inventory investment and business fluctuations, the production smoothing theory and the stock-out avoidance theory take contradictory stances. Decision-making related to inventory investments of corporations is thought to be influenced by both motives, but the relative sizes or directions of their respective influences can differ depending upon the phase of the business cycle. Against this backdrop, this paper differs from existing studies in that it theoretically tests the relative significances of the production smoothing and stock-out avoidance motives in the inventory investment dynamics, while placing its analytical focus on determining the existence and patterns of the asymmetric dynamics of inventory investment over the business cycle phases. To this end this paper sets up a non-linear model that is expanded from the existing linear inventory investment model, and checks whether its predictive power is better than that of the existing model. The results of analysis confirm the nature of the asymmetric dynamics of inventory investment over the business cycle phases. A stock-out avoidance motive appears but there is no significant production smoothing motive in boom times. In downturns, in contrast, the stock-out avoidance motive is insignificant, but a quality of asymmetric dynamics in which changes in inventory cause the deepening of recessions, due to the non-convexity of production costs proposed by Ramey (1991), is detected. This paper confirms that a model considering the asymmetric dynamics of inventory investment can have better predictive power than one that does not consider it, through within-sample and out-of-sample predictions and various predictive power tests. These research results are expected to be useful for economic forecasting, through their enhancement of the understandings of the inventory investment dynamics and of the nature of its business cycle destabilization.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.157-158
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• 2021

Big data in the supply chain mainly comes from four aspects. One is the relevant data inevitably generated in the process of product value transfer of enterprises in the supply chain, such as production equipment quality data, planned procurement data, product data, etc; On the other hand, it is derived from the ERP data of various companies in the supply chain; The third is e-commerce data from the customer, and the last is data from external or manually entered data. A third-party data service center analysis and mining the data to predict and control the inventory in the process of supply chain operation. It brings innovation and change of management technology and way of thinking to the whole supply chain in many aspects, and finally achieves the goal of coordinated inventory and zero inventory of the whole supply chain.