• 한국지능시스템학회논문지
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• 제14권1호
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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.

• 한국건설관리학회논문집
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• 제5권5호
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• pp.143-150
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• 2004

본 연구는 다기준의사결정문제인 건설 프로젝트의 공법선정문제에 있어서 퍼지계층분석법 및 그 결과 생성되는 각 공법별 퍼지 점수의 상대평가를 위해 퍼지 선호도 함수를 적용하여 상대평가를 하고자 하였다. 지금까지의 건설 공법 선정에 대한 퍼지계층분석법에 대한 연구는 대부분 최종적인 공법선정을 위해서 각 공법별로 도출된 퍼지 점수의 순위결정기법으로 절대평가를 수행하였다. 그러나 이러한 기법은 비교 대상공법에 대한 일관적인 순위결과를 산출해 내지 못하므로 결과적으로 공법선정과정의 전반적인 타당성을 저해하는 문제점을 지니고 있었다. 따라서 본 연구에서는 건설 분야의 MCDM(Multiple Criteria Decision Making)에 관한 기존의 연구들을 바탕으로 순위 결정기법에 R.P.R(Relative Preference Ratio)기법을 도입하여 각 공법에 대한 퍼지 점수를 상대 평가함으로써 체계적이고 효율적인 건설 공법선정기법을 제시하였고, 이를 창호공법의 선정문제에 적용하여 그 타당성을 살펴보았다.

• Journal of Mechanical Science and Technology
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• 제20권6호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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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.

• 품질경영학회지
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• 제21권2호
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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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• 제23권1_2호
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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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• 제17권3호
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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.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2012년도 춘계 학술논문 발표대회
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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.

• 자원ㆍ환경경제연구
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• 제15권5호
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• pp.921-937
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• 2006

본 연구는 이산선택 조건부가치측정법에 내재되어 있는 응답자의 선호의 불확실성 문제를 퍼지이론을 통해 해결하려 한 것으로, 멸종위기에 처해 있는 한국산 토종반달곰의 보존에 대한 지불의사액을 추정하는 분석과정에 퍼지소속도 함수를 적용하였다. 퍼지소속도 이론은 애매모호한 상황의 불명확성을 추정하는 방법론으로, 이를 조건부가치측정법에 적용하면 해당 환경재에 대한 지불의사액과 응답자들의 진술에 대한 확신도를 동시에 도출해낼 수 있다. 본 연구를 위해 우리나라 7대 광역시에 거주하는 성인남녀 500명을 대상으로 설문조사를 시행하였으며 양분선택형 조건부가치측정법이 사용되었다. 한국산 토종반달곰 보존에 대한 지불의사액은 가구당 월 9,090원으로 계산되었으며 퍼지소속도함수로 계산된 응답의 확신도는 78%인 것으로 추정되었다.

• Industrial Engineering and Management Systems
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• 제11권1호
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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.