• Journal of the military operations research society of Korea
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• v.11 no.1
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• pp.1-7
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• 1985

A computer-aided simulation model for inventory control was developed using Apple II Plus micro-computer. The model forecasts quarterly demands with Single Exponential Smoothing method and simulates Supply Demand Review and Inventory Level Settings for each items. The simulation is based on the assumption that the demand occurrences have their own probability distributions.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.4
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• pp.398-404
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• 2010

Purpose: Concerns had been voiced about an oversupply of optometrists in Korea. So, this study aimed to forecast the supply and demand for opticians for policy implications. Methods: Baseline Projection model combined with demographic method was adopted as the supply forecasting method and so was a ratio method using the number of physician and population using weight of healthcare utilization. Results: Under the 'physician to optician ratio', there would be a surplus of 83~700 opticians in 2010 and an undersupply of 15 to surplus of 6,118 opticians in 2025. Under the 'population to optician ratio', there would be a surplus of 1,055 opticians in 2010 and surplus of 9,376 opticians in 2025. Conclusions: We concluded that there would be oversupply for opticians until 2025, although the shortage and surplus of opticians might depend on the ratio's criteria. Hence, policies would need to be developed that could solve the imbalance in requirements and supply for opticians.

• Journal of Korean Ophthalmic Optics Society
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• v.13 no.4
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• pp.25-30
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• 2008

Purpose: In this paper, we have analyzed the problems of the Oh's report which is used to the basic data for supply and demand of medical technicians and studied a proposal for improvement to control system and supply and demand of korean optometrists. Methods: We have analyzed errors of Oh's report including supply and demand for medical technicians and management policy, expecting number for future optician, inaccurate estimation by limited data (employment rate, retirement rate, mortality rate) and an incorrect method of measurement for future supply and demand. Results: Oh's report showed the 18% error for estimation of supply which exclude the irregular entrance students. The estimation of supply was calculated by graduation rate 62.6% (college and University of Technology are 78.9% and 85.98% respectively), employment rate 65.8% (the average employment between 2002 and 2007 is 73.96%) and retirement rate is 2.3% (the retirement of pharmacists is 1.3%) but it showed the significant differences to objective data. For estimate the suitable ratio of optometrists to the population, the ratio use of medical facilities by an age group was used, and suggested spectacle wearers 1,280 persons (populations 2,928 persons) per optometrist but the different from reference of Germany (4,706 persons), America (1,789 persons) and Korea (1,825 persons/an optometrist) are applied to estimation on supply. This report applied the low employment rate and argued that maintain the present situation, but claimed that utilize unemployment persons. The above result has induced double weighting effect on estimation of supply. Conclusions: To solve the related problems of supply and demand, we have to make a search for exact data and optimum application model, have to take an example of nation similar job category as Germany and the research result of the job satisfaction into consideration. After we get the integrated research result, we must carried out the policy with fairness and balance for the estimation of supply and demand. Therefore exact research is required prior to beginning policy establishment, government and related group have to make a clear long-term plan and permanent organization for medical technician to establish supply and demand of medical technician.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2245-2253
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• 2018

With the increase of electrical consumption and the unbalance of power demand and supply, power reserve rate is getting smaller and also the reliability of the power supply is getting deteriorated. Under this circumstance, the electrical energy storage (EES) System is considered as one of essential countermeasure for demand side management. This paper proposes efficient evaluation algorithms of multiple functions for EES systems, especially the secondary battery energy storage systems, in the case where they are interconnected with the power distribution systems. It is important to perform the economic evaluation for the new energy storage systems in a quantitative manner, because they are very costly right now. In this paper, the multiple functions of EES systems such as load levelling, effective utilization of power distribution systems and uninterruptible power supply are classified, and then the quantitative evaluation methods for their functions are proposed. From the case studies, it is verified that EES systems installed at distribution systems in a dispersed manner have multiple functions involved with direct and indirect benefits and also they can be expected to introduce to distribution systems with respects to economical point of view.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.280-295
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• 2022

This paper contains an introduction to industrial problems, solutions, and results conducted with the Korea Association of Machinery Industry. The client company commissioned the problem of upgrading the method of identifying global supply risky items. Accordingly, the factors affecting the supply and demand of imported items in the global supply chain were identified and the method of selecting risky items was studied and delivered. Through research and discussions with the client companies, it is confirmed that the most suitable factors for identifying global supply risky items are 'import size', 'import dependence', and 'trend abnormality'. The meaning of each indicator is introduced, and risky items are selected using export/import data until October 2022. Through this paper, it is expected that countries and companies will be able to identify global supply risky items in advance and prepare for risks in the new normal situation: the economic situation caused by infectious diseases such as the COVID-19 pandemic; and the export/import regulation due to geopolitical problems. The client company will include in his report, the method presented in this paper and the risky items selected by the method.

• Knowledge Management Research
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• v.15 no.3
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• pp.169-188
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• 2014

Big data seems to change knowledge management system and method of enterprises to large extent. Further, the type of method for utilization of unstructured data including image, v ideo, sensor data a nd text may determine the decision on expansion of knowledge management of the enterprise or government. This paper, in this light, attempts to figure out the prediction model of demands and supply for big data market of Korea trough data mining decision making tree by utilizing text bit data generated for 3 years on web and SNS for expansion of form for knowledge management. The results indicate that the market focused on H/W and storage leading by the government is big data market of Korea. Further, the demanders of big data have been found to put important on attribute factors including interest, quickness and economics. Meanwhile, innovation and growth have been found to be the attribute factors onto which the supplier puts importance. The results of this research show that the factors affect acceptance of big data technology differ for supplier and demander. This article may provide basic method for study on expansion of analysis form of enterprise and connection with its management activities.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.41-47
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• 2015

In recent years, energy supply cases to take advantage of EMS(Energy Management System) are increasing according to high interest of energy efficiency. The important factor for essential and economical EMS operation is the supply and demand plan the hourly power demand of building load using the hierarchical clustering method of variety statistical techniques, and use the real historical data of target load. Also the estimated results of study are obtained the reliability through separate tests of validity.

• Korean Management Science Review
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• v.19 no.2
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• pp.75-89
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• 2002

According to the fast-paced environment of information technology and improving customer services, the design activities of logistics systems improve customer centric services and delivery performance implementing e-logistics system. The fundamental design issues that arise in the delivery system planning are optimizing the system with minimum cost and maximum throughput and service level. This study is concerned with the integrated model development of delivery system with customer responsive service level for DCM, Demand Chain Management. We used a two-step approach for this study. First, we formulated the supply. center facility planning using stochastic set-covering problem and assigned the customers to the supply center using clustering algorithm. Second, we developed vehicle delivery planning for a supply center based on GIS, GIS-VRP. Also we developed a GUI-type computer program for proposed method for supply center problem using GIS and Geo-DataBase of Busan area. The computational results showed that the proposed method was very effective on a set of test problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.11-21
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• 1999

The purpose of this study is to present the method to select optimal size for the industrial products which are closely related to human's body size. For this purpose, human factors such as body characteristics, body features, and preference in product selection which needs to be considered in setting standards were analyzed. This analysis is to select optimal size to minimize losses caused by the difference of size between demand by the customers and supply from the manufacturers. Using loss function, repetitive calculation process algorithm by using bisearch method was applied in selecting the sizes of demand and supply which minimize the total expected losses. For cumulative normal distribution probability, IMSL routine DNORDF was used. In case study, comparison has been made between the result which was calculated using presented algorithm and the results calculated by the process currently used by KS and ISO by measuring aged women's body size in human factors side and sorting them through the factor analysis and cluster analysis for feature factor extraction. Thus, they can be used as a basis for establishing industrial product standards.