• International Commerce and Information Review
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• v.8 no.3
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• pp.277-297
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• 2006

Joined WTO, China has revised or removed continuously some of existing enter barriers which have been protecting Chinese distribution market. Chinese government intend to open completely it's distribution market in 2007. Such as the open policy of Chinese distribution impact on Korean firms which invest in China. in order to occupy China's market, Korean firms needs to prepare counterplan on change of China's distribution environments. China's distribution environment is uncertain on account of remaining communism system even though opening it's distribution market. The purpose of this paper is to suggest diverse counterplan of Korean firms and answer how Korean firms can enter the China's distribution market successfully. through exmaninig how China's distribution channel is formulated and implemented. this study exhibits a model for strategy of Korean firms and shows implementations schemes.

• International Journal of Reliability and Applications
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• v.16 no.2
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• pp.81-98
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• 2015

The Exponentiated Gamma (EG) distribution is one of the important families of distributions in lifetime tests. In this paper, a new generalized version of this distribution which is called kumaraswamy Exponentiated Gamma (KEG) distribution is introduced. A new distribution is more flexible and has some interesting properties. A comprehensive mathematical treatment of the KEG distribution is provided. We derive the $r^{th}$ moment and moment generating function of this distribution. Moreover, we discuss the maximum likelihood estimation of the distribution parameters. Finally, an application to real data sets is illustrated.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.102-108
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• 2002

Due to the many attractive aspects of DG in the future power distribution system, distribution automation will be a center hub of integration of the distribution system and resources to satisfy the various needs of customers in a competitive and deregulated environment. In this paper, operation strategies are presented which use network reconfiguration of the automated distribution systems with DG as a real-time operation tool for loss reduction and service restoration from the view of distribution operation. The algorithms and operation strategies of an automated distribution system with DG are introduced to achieve the positive effects of DG in distribution systems. A simple case study shows the effectiveness of the proposed operation strategies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.19-27
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• 2008

This paper addresses determining the location of the distribution centers in a discrete dynamic distribution system. In discrete and finite time horizon, the demands of retailers are dynamic for the periods. Some locations among the retailers can be chosen for the role of the distribution centers at the beginning of each period. The distribution centers have to be located at the location of minimizing logistics cost. Logistics cost factors are the operation cost and the fixed cost of distribution center, and the transportation cost. The distribution centers of minimizing sum of operation cost, fixed cost and transportation cost are determined among retailers in each period for the planning period. A mathematical model was formulated and a dynamic programming based algorithm was developed. A numerical example was shown to explain our problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.85-94
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• 2003

In this paper, a mathematical model is developed for economic design of multi-stage distribution system that consists of factory, central distribution centers, local distribution centers and retailers. The retailers are supplied products from different stage suppliers according to order size. The retailers are supplied products from factory if demand amount is large, central distribution center if medium, local distribution center if small. The economic design is to determine the economic size of facility factors that consist of distribution system. The cost factors are transportation cost from supply places to demand places, handling cost at distribution centers and inventory holding cost at retailers. It is to determine the transportation route of each retailer, the size and number of the vehicle at factory and distribution centers, the handling amount at distribution centers in order to minimize the total costs. The mathematical model is represented, the solution procedure is developed, and a numerical example is shown.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Proceedings of the KIEE Conference
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• summer
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• pp.73-75
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• 2004

This paper presents the ability and the application of software packages for distribution planning which are DISPLAN(Distribution Planning System) and DLPLAN(Distribution Line Planning System) developed in KEPCO. After calculating size and position of maximum load by administration section for distribution, it forecasts the demand of distribution load considering growth location, increment, new load plan, etc of load by annual. Also it calculates distribution loss, voltage drop using modeled distribution line by you, and support for establishment and enlargement plan of substation and distribution line, decision of most optimal path. And it presents the abstract of used algorithm to develop this system.

• Wind and Structures
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• v.28 no.6
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• pp.369-380
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• 2019

Statistical distributions are very useful in describing wind speed characteristics and in predicting wind power potential of a specified region. Although the Weibull distribution is the most popular one in wind energy literature, it does not seem to be able to perfectly fit all the investigated wind speed data in nature. Thus, many studies are still being conducted to find flexible distribution for modelling wind speed data. In this study, we propose a new Odd-Burr Rayleigh distribution for wind speed characterization. The Odd-Burr Rayleigh distribution with two shape parameters is flexible enough to model different shapes of wind speed data and thus it can be an alternative wind speed distribution for the assessment of wind energy potential. Therefore, suitability of the Odd-Burr Rayleigh distribution is investigated on real wind speed data taken from different regions in the South Africa. Numerical results of the conducted analysis confirm that the new Odd-Burr Rayleigh distribution is suitable for modelling most of the considered real wind speed cases and it also can be used for predicting wind power.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.509-522
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• 2018

Purpose: The purpose of this study was to propose more accurate mathematical model which can represent result of government quality assurance activity, especially corrective action and flaw. Methods: The collected data during government quality assurance activity was represented through histogram. To find out which distributions (Poisson distribution, Zero-Inflated Poisson distribution) could represent the histogram better, this study applied Pearson's correlation coefficient. Results: The result of this study is as follows; Histogram of corrective action during past 3 years and Zero-Inflated Poisson distribution had strong relationship that their correlation coefficients was over 0.94. Flaw data could not re-parameterize to Zero-Inflated Poisson distribution because its frequency of flaw occurrence was too small. However, histogram of flaw data during past 3 years and Poisson distribution showed strong relationship that their correlation coefficients was 0.99. Conclusion: Zero-Inflated Poisson distribution represented better than Poisson distribution to demonstrate corrective action histogram. However, in the case of flaw data histogram, Poisson distribution was more accurate than Zero-Inflated Poisson distribution.

• Journal of Distribution Science
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• v.10 no.10
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• pp.5-9
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• 2012

Purpose - The purpose of this study is to explore, examine, and analyze Journal of Distribution Science and its articles based on five key factors of journal selection process by Thompson and to provide foundations for further knowledge creation and theory building in the areas of distribution and distribution science. Research design, data, methodology - This study used an exploratory case study method to engage article analysis and reviews of Journal of Distribution Science. Thompson's five journal selection factors were used as criteria for the journal and article analyses and review. Results - Journal of Distribution Science is currently meeting or at least in the progress of meeting the following factors: timeliness of publication, international editorial convention, international diversity, and citation analysis. However, JDS is short of meeting the factor of editorial content. The research topics were not new, emerging, and/or distinctive, and they were not directly associated with specific region or country other than Korea. Conclusions - The findings from this study could lead the field of distribution to reexamine the core knowledge, to reestablish the fundamental concepts and principles, to formulate and propose academically and practically sound research methods, and to develop and focus on unique research topics in the area of distribution.