• The Journal of Asian Finance, Economics and Business
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• 제6권2호
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• pp.213-221
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• 2019

The study aims to investigate some criteria of supplier selection in the textile and apparel (T&A) sector in Vietnam. Most research on supplier selection criteria for T&A sector was mainly conducted based on the review of literature. Therefore, the purpose of this study is to explore these criteria based on a framework in which an integrated approach of qualitative and quantitative was employed. First, an in-depth interview was used to explore what supplier selection criteria T&A companies were utilized after the literature on supplier selection criteria had been reviewed. Next, a prequestionnaire was built and sent to some practitioners and experts for their revision. Then, a pilot survey of 31 T&A companies with numerous statistical tests was conducted to validate the questionnaire. Finally, an official study of 282 respondents was conducted to determine supplier selection criteria which are best suited for T&A companies through exploratory factor analysis. The findings of the study suggest that there are eight supplier selection criteria including Quality, Cost, Delivery, Service, Capability, Company's image, Relationship, and Sourcing country. Each criterion comprises certain sub-criteria to make the supplier selection criteria set more comprehensive. The findings will be a contribution to the selection process of T&A companies as they can utilize these criteria to select capable suppliers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.137-139
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• 2017

Modern manufacturing fields have been changed to use optimal manufacturing volume on the optimal demand prediction. This research is to compare the prediction capability of various prediction methods. And then, it is to suggest a flexible selection of the optimal prediction method according to optimal prediction capability.

• Communications for Statistical Applications and Methods
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• 제17권1호
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• pp.17-27
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• 2010

Feature selection and feature weighting are useful techniques for improving the classification accuracy of k-Nearest Neighbor (k-NN) classifier. The main propose of feature selection and feature weighting is to reduce the number of features, by eliminating irrelevant and redundant features, while simultaneously maintaining or enhancing classification accuracy. In this paper, a novel hybrid approach is proposed for simultaneous feature selection, feature weighting and choice of k in k-NN classifier based on Genetic Algorithm. The results have indicated that the proposed algorithm is quite comparable with and superior to existing classifiers with or without feature selection and feature weighting capability.

• Journal of Korea Technology Innovation Society
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• 제1권3호
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• pp.326-337
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• 1998

This study aims to propose the model of functional specialization for university and the selection of research university in Korea. This study propose that we diversify universities into three categories ; research university, educational university, and technical university. Considering the current research capability and future research prospect of Korean universities, this study found that 8 universities could be classified as research university. However, in light of a balanced regional growth of research system two more universities could be designated as research university.

• Journal of Korean Society for Quality Management
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• 제26권1호
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• pp.1-10
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• 1998

Su, pp.ier quality plays a major role in the evaluation of su, pp.iers, making it very necessary to develop a proper quality measure useful in selecting su, pp.iers that is able to meet quality specification of the customer. In this paper, we present a measure of the overall quality performance which is a weighted geometric mean of the process capability indices of the quality characteristics of a su, pp.ier. This measure can be used both as a measure of su, pp.ier selection for the customer and as a measure for the self-analysis of the quality performance for the su, pp.ier.

• Journal of the Korean Society for Precision Engineering
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• 제9권3호
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• pp.53-60
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• 1992

This paper deals with developing an Expert system for tool selection using knowledge base system approach, and its application. For the sake of building of knowledge base, the information from process through sensor, tool handbook and interview with expert are referrenced and managed. The system developed shows good application flexibility in providing the actual cutting process with the selection of tool(insert, holder) and cutting conditions(feed, speed, rake type, and so on), is found as a useful system for real-time machining process. The Expert system for tool selection is written in TURBO PROLOG ver. 2.0 for inference engine capability, and can be run in interactive mode for user friendliness. In order to apply the system developed in actual cutting process, more parameters should be considered and scrutinized, and the system should be further extended in modular basis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3501-3523
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• 2017

It is a classical integer optimization difficulty to design an optimal selection scheme in cooperative relay networks considering co-channel interference (CCI). In this paper, we solve single-objective and multi-objective relay selection problem. For the single-objective relay selection problem, in order to attain optimal system performance of cooperative relay network, a novel quantum differential evolutionary algorithm (QDEA) is proposed to resolve the optimization difficulty of optimal relay selection, and the proposed optimal relay selection scheme is called as optimal relay selection based on quantum differential evolutionary algorithm (QDEA). The proposed QDEA combines the advantages of quantum computing theory and differential evolutionary algorithm (DEA) to improve exploring and exploiting potency of DEA. So QDEA has the capability to find the optimal relay selection scheme in cooperative relay networks. For the multi-objective relay selection problem, we propose a novel non-dominated sorting quantum differential evolutionary algorithm (NSQDEA) to solve the relay selection problem which considers two objectives. Simulation results indicate that the proposed relay selection scheme based on QDEA is superior to other intelligent relay selection schemes based on differential evolutionary algorithm, artificial bee colony optimization and quantum bee colony optimization in terms of convergence speed and accuracy for the single-objective relay selection problem. Meanwhile, the simulation results also show that the proposed relay selection scheme based on NSQDEA has a good performance on multi-objective relay selection.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1377-1382
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• 2015

Power system restoration following a massive blackout starts with re-energizing Primary Restorative Transmission (PRT) systems at first. As power systems have been gradually enlarged and become more complex, periodical evaluation and reassignment of PRTs are needed. So far it has been decided by try and error approach by corresponding human experts to analyze and evaluate them. This paper presents an intelligent system that finds optimal primary restoration paths using analytic and heuristic knowledge from PSS/E data, and suggests an optimal PRTs depending on the condition of Ferranti effect or a reactive power capability margin of black-start generator. This system was tested in Korea Electric Power system, and showed a promising result.

• Proceedings of the KSR Conference
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• 한국철도학회 2009년도 춘계학술대회 논문집
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• pp.1914-1923
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• 2009

KORAIL continuously drives practical reforms of change and originality both internally and externally for the purpose of adapting to rapidly changing circumstance and promote productivity of the organization. Various management strategies are needed to increase its productivity, yet the fist thing to be considered is to select talented human resources. A selection of the human resource should be conducted based on 3R(Right People, Right Place, Right Time). This study empirically analyzes through actual study how the method of new employment introduced on January 1, 2005 positively affects capability and productivity of each member of KORAIL. The area of this study is defined centering on the standard of new employment, capability of personnel, and productivity of the organization. Also, the improvement of new employment standard of KORAIL is suggested as significance of the standard was verified through survey of the standard, the capability and the productivity conducted to KORAIL working personnel.

• Journal of the Korean Operations Research and Management Science Society
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• 제39권3호
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• pp.51-61
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• 2014

In this paper, we deal with developing a cost estimation relationships (CER) for Korean maneuverable weapons systems using historical production cost. To develop the CER, we collected the historical data of the production cost of four tanks and five armored vehicles. We also analyzed the Required Operational Capability (ROC) of the weapons systems and chose cost drivers that can compare operational capabilities of the weapons systems We used Forward selection, Backward selection, Stepwise Regression and $R^2$ selection as the cost drivers which have the greatest influence with the dependent variables. And we used Principle Component Regression, Robust Regression and Weighted Regression to deal with multicollinearity and outlier among the data to develop a more appropriate CER. As a result, we were able to develop a production cost CER for Korean maneuverable weapons systems that have the lowest cost errors. Thus, this research is meaningful in terms of developing a CER based on Korean original cost data without foreign data and these methods will contribute to developing a Korean cost analysis program in the future.