• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.69-74
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• 2004

A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.143-150
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• 2004

Nowaday, The tendency of complexity and extension of construction fields increase the need for efficient works managements like a construction management. Consequently, by the introduction of Decision-Making Theories, researches for improving construction field's efficiencies are actively performed. Fuzzy Analytical Hierarchy Process method is invented, so that describes a decision maker's ambiguous linguistic judgment with fuzzy numbers. but most of researches on Fuzzy-AHP use symmetric triangular fuzzy function for estimating each evaluation item with the consequence that exact judgments are impossible. those limits are caused by the point that employed fuzzy ranking methods can not support dissymmetric fuzzy numbers. In this research, we aims to overcome this problem with R.P.R(Relative Preference Ratio) method and suggest improved Fuzzy-AHP method which can use dissymmetric fuzzy triangular numbers.

• Journal of Mechanical Science and Technology
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• v.20 no.6
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• pp.731-737
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• 2006

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.640-645
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• 1998

A Sequencing problem is one to find an ordered sequence of some entities which maximizes (or minimize) some objective function. This paper introduces an new type of sequencing problems, named a Sequencing problem with fuzzy preference relation is previded for the evaluation of the quality of sequences, It presents how such a problem can be formulated in the point of objective function. In addition, it proposes a genetic algorithm applicable to such a sequencing problem.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.194-214
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• 1993

This paper purports to study on interactive fuzzy goal programming model which leads to the compromise solution which the decision maker satisfies through the interactive approach. We also attempted to calculate local proxy preference function from utility function of sum-of-logarithms in connection with marginal rate of substitution and interactive approach for the purpose of applying weight of multiobjective function. In an attempt to grasp compromise solution from fuzzy efficient solution, we decided to take the interactive method and presented stopping rule for this.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.547-552
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• 2007

In this note, we extends some of the results of Liu [Fuzzy Sets and systems 157 (2006) 869-878]. This extension consists of a simple proof involving weighted functions and their preference index. We also give an elementary simple proof of the maximum entropy weighting function problem with a given preference index value without using any advanced theory like variational principles or without using Lagrangian multiplier methods.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.991-997
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• 2006

Recently, Liu (2005) proposed a special type of weighting function under a given preference index level with the minimal variability similar to the minimal variability OWA operator weights problem proposed by Fuller and Majlender (2003). He solved this problem using a result of classical optimal control theory. In this note, we give a direct elementary proof of this problem without using any known results.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.11-14
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• 2012

The category for waterproofing is one of construction process most affected by falling-off in price competitiveness, construction quality, and material performance. Therefore, in order to select of waterproofing construction firms, it is necessary to consider Incorporating both price competitiveness and construction quality. In this article, I would like to analyze 10 Factors for Selecting using fuzzy-AHP model, including the survey of the waterproofing experts. This fuzzy-AHP model can be shown to calculate the fuzzy trigonometrical function to reflect weights for preference of 10 factors for the waterproofing construction firms. It was found from the result that waterproofing construction firms was searched order of priority for select by fuzzy-AHP model.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.921-937
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• 2006

In this paper, we apply fuzzy theory in a discrete choice Contingent Valuation Method(CVM) in order for dealing preference uncertainty problem. Fuzzy membership function is used in an empirical analysis to estimate the willingness-to-pay(WTP) for the preservation of the endangered Asiatic Black Bear in Korea. The estimated WTP was about 9,090 Korea Won per household with 78 percent of confidence level. The advantage of applying fuzzy theory in the valuation method could be found in its ability to measure the confidence level of the estimated WTP.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.1-10
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• 2012

Supplier selection is an essential task within the purchasing function of supply chain management because it provides companies with opportunities to reduce various costs and realize stable and reliable production. However, many companies find it difficult to determine which suppliers should be targeted as each of them has varying strengths and weaknesses in performance which require careful screening by the purchaser. Moreover, information required to assess suppliers is not known precisely and typically fuzzy in nature. In this paper, therefore, fuzzy multi-objective linear programming (fuzzy MOLP) is presented under fuzzy goals: cost minimization, service level maximization and purchasing risk. To solve the problem, we introduce an enhanced two-phase approach of fuzzy linear programming for the supplier selection. In formulated problem, Analytical Hierarchy Process (AHP) is used to determine the weights of criteria, and Taguchi Loss Function is employed to quantify purchasing risk. Finally, we provide a set of alternative solution which enables decision maker (DM) to select the best compromise solution based on his/her preference. Numerical experiment is provided to demonstrate our approach.