• IE interfaces
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• v.19 no.2
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• pp.106-116
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• 2006

In this study, the priority of risk factors in supplying water through water supply pipeline network was evaluated by PROMETHEE and ANP multi-criteria decision analysis. We chose 'corrosion', 'burst' and 'water pollution' in pipe as major reference criteria and selected eight risk factors to evaluate the priority, and then we compared the results of PROMETHEE with those of ANP. We also analyzed the results of the sensitivity analysis by changing the weights and parameters of preference functions in PROMETHEE. We investigated the possibility of integrating two methods by using the results of ANP as the weights of preference function in PROMETHEE. The priority of risk factors for supplying municipal water which is evaluated by this study may provide basic data to establish a contingency plan for accidents, or to establish the specific emergency response procedures.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.358-380
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• 2016

In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics rate of the processed text. As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging results with an F-measure of more than 80%.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.197-211
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• 2002

In this paper, we propose a multi-Criteria decision making approach to address the problem of finding the best possible solution in credit unions. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses the Euclidean distance method to measure distances of all possible solutions from the identified ideal solution. The possible optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the Problem.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.126-135
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• 1992

The decision making process for production planning in FMS usually involves multiple conflicting objectives and criteria. This study consists of prescreening and analytical phase. In the prescreening phase, criteria are used to reduce the set of alternative system configuration down to a small number of candidates. After this phase, a multiobjected programming model is formulated for each remainning configuration.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.423-428
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• 2004

Flooding is one of the main causes of loss of lives and properties among various natural disasters in Korea. Flood risk maps are currently being produced in Korea but the progress is slow considering the necessity to map at nationwide scale. In this study, GIS-based multi-criteria decision making process which is normally used for resource management and site analysis was applied to locate flood vulnerable areas. Past records of flooding maps were analysed to extract topographic characteristics of flooded areas. The extracted characteristics were then set as criteria for flooding analysis using the Fuzzy and Analytic Hierarchy Process(AHP) methodology. Results from this study showed that an improved phased action plan was possible, because the flood vulnerable areas are shown in varying degrees of uncertainty unlike the conventional Boolean type GIS layer superimposition analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6B
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• pp.551-563
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• 2011

Water resource projects need an enormous national budget. Therefore, a reasonable and reliable decision making is required for the planning of water resource projects, but decision making has been mostly performed by economic analysis. The objective of this study is to develop a Multi-criteria Decision Making(MCDM) model which can assess the project in various aspects for the selection of preferable alternative and determination of investment priority in water resource projects. In this study, the criteria involves economic feasibility, policies, vulnerability, and sub-items which have weights obtained from the expert survey for the consistent evaluation. We also derived the utility function considering risk trend of each item based on the expert survey. Then, the total score was estimated by weights of each item and utility score of each attribute. The results show that vulnerability is a major contributor for the criteria. This study will contribute to the selection of proper water resource projects considering efficiency of project and fairness for vulnerable area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.293-302
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• 2019

In mountain accident events, it is important for the search team commander to determine the search area in order to secure the Golden Time. Within this period, assistance and treatment to the concerned individual will most likely prevent further injuries and harm. This paper proposes a method to determine the search priority area based on missing persons behavior and missing persons incidents statistics. GIS (Geographic Information System) and MCDM (Multi Criteria Decision Making) are integrated by applying WLC (Weighted Linear Combination) techniques. Missing persons were classified into five types, and their behavioral characteristics were analyzed to extract seven geographic analysis factors. Next, index values were set up for each missing person and element according to the behavioral characteristics, and the raster data generated by multiplying the weight of each element are superimposed to define models to select search priority areas, where each weight is calculated from the AHP (Analytical Hierarchy Process) through a pairwise comparison method obtained from search operation experts. Finally, the model generated in this study was applied to a missing person case through a virtual missing scenario, the priority area was selected, and the behavioral characteristics and topographical characteristics of the missing persons were compared with the selected area. The resulting analysis results were verified by mountain rescue experts as 'appropriate' in terms of the behavior analysis, analysis factor extraction, experimental process, and results for the missing persons.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.891-897
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• 2021

In this paper, we propose a destination optimal route algorithm for providing route finding service for the transportation handicapped by using the multi-criteria decision-making technique and the modified A-STAR optimal route search algorithm. This is a method to set the route to the destination centering on safety by replacing the distance cost of the existing A-STAR optimal route search algorithm with the safety cost calculated through AHP/TOPSIS analysis. To this end, 10 factors such as road damage, curb, and road hole were first classified as poor road factors that hinder road driving, and then pairwise comparison of AHP was analyzed and then defined as the weight of TOPSIS. Afterwards, the degree of driving safety was quantified for a certain road section in Busan through TOPSIS analysis, and the development of an optimal route search algorithm for the transportation handicapped that replaces the distance cost with safety in the finally modified A-STAR optimal route algorithm was completed.