• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.117-124
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• 2010

The military vehicles are an inevitable resource that is indispensible to successfully perform modern wars. Military vehicles used in the Korean Army are the copycats of American out-dated military vehicles, but limited to fulfill the specific requirements by the operators. Korean army are nowadays trying to launch a new developmental plan for military vehicles of new concepts by the Korean Army. This article, hence, extracts the necessary factors upon the advancement of military vehicles by the expertises with the operation of military vehicles as well as sufficient experiences about maintenance. Suggesting and setting up the priority, the result makes practical application for the decision of the development of military vehicles.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.29-46
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• 2007

This paper makes an attempt to compare the two important methods for finding solutions of multi-item inventory problem with more than one conflicting objectives. Panda et al.[9] discusses a distance-based method to find the best possible compromise solution with variation of priority under the given weight structure. In this paper, the problem in [9] is revisited through the Pareto-optimal front of genetic algorithm with the help of a situation of retail stocking of FMCG business. The advantages of using the solutions from the perspective of the decision maker obtained through multi-objective optimization are highlighted in terms of population search, weighted goals and priority structure, cost, set of compromise solutions along with prevention of stock-out situation.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.201-218
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• 1999

The article contains an introduction of possibility of applying Multi-Attribute Utility Theory(MAUT) for priority setting of R&D projects. MAUT is compared with AHP, which is widely used recently. These two techuiques are applied to set priorities of R&D projects In a Government-funded Research Institute. Six criteria are chosen from consultation with decision makers. They are composed of 1) validity as representative projects, 2) possibility of resource mobilization, 3) spillover effect of developed technologies, 4) possibility of success, 5) scope of participation and 6) clarity of research goal. To set priorities of R&D projects, SMART(Simple MultiAttribute Rating Technique) and DVM(Difference Value Measurement) out of many MAUT methods are used to design the utility function and to determine the weights among criteria. The aggregation model is additive on the assumption the criteria are independent. AHP executes pairwise comparisons for criteria and alternatives. From the results of the case study, the results and theoretical characteristics are compared.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.235-240
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• 2013

Cloud systems are popular computing environment because they can provide easy access to computing resources for users as well as efficient use of resources for companies. The resources of cloud computing are heterogeneous and jobs have various characteristics. One such issue is effective job scheduling. Scheduling in the cloud system may be defined as a multiple criteria decision model. To address this issue, this paper proposes a priority-based two-step job scheduling algorithm. On the first level, jobs are classified based on preference. Resources are dedicated to a job if a deadline failure would cause severe results or critical business losses. In case of only minor discomfort or slight functional impairment, the job is scheduled using a best effort approach. On the second level, jobs are allocated to adequate resources through their priorities that are calculated by the analytic hierarchic process model. We then analyze the proposed algorithm and make a scheduling example to confirm its efficiency.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04a
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• pp.687-690
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• 2002

In this paper, we present a novel semaphore implementation scheme which shortens finish time of high priority tasks and improves reliability of a system. The real-time systems have time constraints. Especially, the task with hard real-time constraints must meet its deadline. Consequently, managing shared resources is considered guaranteeing mutual exclusion as well as meeting task's deadline under unfavorable condition. According to the number and sort of the locked semaphores under the event occurred, this paper presents the reduction of the finish time of high priority task by decision whether the context switched or not. The experimental results show that the proposed method gives performance improvements in finish time of high priority tasks of about 11% over zuberi[4] method.

• Journal of the Korean association of regional geographers
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• v.17 no.1
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• pp.58-74
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• 2011

This study analyzed and compared the importance and priority of location decision factors in Foreign Direct Investment Firms managing the manufacturing business in the nation's southeastern economic zone, and in expert group by using AHP analytical technique based on examining the location theory and the prior research of real estate for industry. Also, it analyzed difference in importance and priority for location factors by corporate scale, by business category, and by location type targeting only foreign direct investment firms, and offered references necessary for location decision-making. In addition, to elicit useful information for policy related to location decision factors for foreign direct investment firms, the implications were elicited by analyzing the results recognized between foreign direct investment firms and expert group on information elements regarding investment satisfaction, business bottlenecks, and location decision process. The considerable gap was indicated in importance and priority of location decision factors considered between the nation's foreign direct investment firms and real-estate expert group for industry. As a result of analyzing by reflecting the corporate characteristic variable in location assessment model unlike before, the importance of the competitive advantage factor and the business strategic factor was indicated to be very high.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.275-298
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• 2014

The purpose of this study is to verify the difference between the importance level and the satisfaction level of each purchase decision factor of smart phone. Through review of literatures about purchase decision factors, we have derived about attributes of 6 factors. T-test, importance performance analysis (IPA), and regression analysis were conducted to identify priorities among the details of the importance and satisfaction and to analyze the effect relationship between satisfaction of each factor and overall satisfaction. Looking at a few high-priority order, battery capacity, memory capacity, fast and accurate repair, the adequacy of the repair cost, and processor in the top five factors were shown to be an important factor when purchasing smart phones. The results of this study can provide the marketing strategies for smart phone suppliers. In addition, these results imply what factors of smart phones should be more considered before launching into chinese smart phone market.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.375-381
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• 2014

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.1
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• pp.97-106
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• 2015

A CCTV inspection method has been widely used to assess sewer condition and performance, but Korea lacks a proper decision support system for prioritizing sewer repair and rehabilitation (R&R). The objective of this paper is to introduce the results that we have developed in the Sewer Condition Assessment and Rehabilitation Decision-making (SCARD) Program using MS-EXCEL. The SCARD-Program is based on a standardized defect score for sewer structural and hydraulic assessment. Priorities are ranked based on risk scores, which are calculated by multiplying the sewer severity scores by the environmental impacts. This program is composed of three parts, which are decision-making for sewer condition and performance assessment, decision-making for sewer R&R priority assessment, and decision-making for optimal budget allocation. The SCARD-Program is useful for decision-makers, as it enables them to assess the sewer condition and to prioritize sewer R&R within the limited annual budget. In the future, this program logic will applied to the GIS-based sewer asset management system in local governments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.