• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.742-748
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• 1994

Scientific involvement in complex decision-making systems, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced, the systems are become more complex. This paper presents a fuzzy dependence relation model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation in fuzzy system theory. For the application of the model a numerical example is quoted.

• Communications of the Korean Mathematical Society
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• v.32 no.4
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• pp.1077-1097
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• 2017

In this research article, we introduce certain concepts, including domination, total domination, strong domination, weak domination, edge domination and total edge domination in m-polar fuzzy graphs. We describe these concepts by several examples. We investigate some related properties of certain dominations in m-polar fuzzy graphs. We also present a decision making method based on domination in m-polar fuzzy graphs.

• Journal of Information Technology Applications and Management
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• v.19 no.3
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• pp.19-30
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• 2012

Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper is aimed to present a fuzzy decision making approach to deal with the material selection in engineering design problems. A fuzzy multi criteria decision-making model is proposed for solving the material selection problem. The proposed model makes use of fuzzy TOPSIS (Technique for Order reference by Similarity to Ideal Solution) with trapezoidal numbers for evaluating the criteria and ranking the alternatives. And result is compared with fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, means Multi criteria Optimisation and Compromise Solution) which is proposed by Jeya Girubha and Vinodh [2012]. The present paper is aimed to also improve literature of fuzzy decision making for material selection problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.41-50
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• 1997

In this paper, we presents the method for finding the compensatory solution for fuzzy multiobjective nonlinear programming problem with fuzzy parameters involved in the problem-formulation process and fuzzy equal goals of the decision maker for each of the objective functions. The fuzzy parameters in the objective functions and the constraints characterized by fuzzy numbers. The proposed method can be applied to case with multiobjective problems and guarantee an efficient solution. An illustrative numerical example is presented.

• International Journal of Reliability and Applications
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• v.2 no.2
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• pp.137-146
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• 2001

In general, analysis of the decision problems in nuclear system management involves a simultaneous consideration of various criteria and decision alternatives. Sometimes, it is a complex, unstructured, ill-defined process incorporating the multi-criteria and the data of impreciseness. To cope with this analysis, a fuzzy hierarchical analysis methodology is proposed and demonstrated with a simple example.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.59-68
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• 1998

The goal of data mining is to develop the automatic and intelligent tools and technologies that can find useful knowledge from databases. To meet this goal, we propose an efficient data mining algorithm based on the fuzzy decision tree. The proposed method combines comprehensibility of decision tree such as ID3 and C4.5 and representation power of fuzzy set theory. So, it can generate simple and comprehensive rules describing data. The proposed algorithm consists of two stages: the first stage generates the fuzzy membership functions using histogram analysis, and the second stage constructs a fuzzy decision tree using the fuzzy membership functions. From the testing of the proposed algorithm on the IRIS data and the Wisconsin Breast Cancer data, we found that the proposed method can generate a set of fuzzy rules from data efficiently.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.549-556
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• 2006

In this paper, we consider interval-valued Choquet integrals and fuzzy measures. Using these properties, we discuss some applications of them in multicriteria decision aid. In particular, we show how these interval-valued Choquet integrals can model behavioral analysis of aggregation in ulticriteria decision aid.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.158-164
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• 2007

Supply Chain Management (SCM) system is a critical investment that can affect the competitiveness and performance of a company. Selection of a right SCM system is one of the critical issues. This paper presents the characteristic factors of SCM system and a Fuzzy AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. This study focuses on quantitative factors, applying the fuzzy concept to various evaluative factors. The proposed model can systematically construct the objectives of SCM system selection to achieve the business goals. A empirical example demonstrates the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.91-105
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• 2008

Nowadays, circulation industry is taking charge of important role in improvement of competitive power on the manufacturing industry and public welfare increase of consumer, price stabilization, employment creation and so on. A lot of research have been progressing for formation of total circulation complex, but decision making for selection of location on some facility is only calculated the optimum value when correct data values are inserted. However, a lot of decision making is accomplished in situation that have little knowledge of objective and constraints and as real world is also evaluated inclusive of analyst's subjectivity about variable, indefinite and fuzzy part, so it is decreasing a reliability on evaluation result and complicating objective evaluation on various effect and negative impact. Accordingly, from under like this situation, this study is to develop location decision model of circulation complex using fuzzy theory from the intention for the most reasonable decision making in fuzzy situation based on decision making problem on conventional location and size decision that did to be satisfactory constraints necessarily.