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Proceedings ArticleDOI

Multicriteria analysis with fuzzy pairwise comparison

Hepu Deng
- Vol. 2, pp 726-731
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TLDR
The result shows that the approach developed is simple and comprehensible in concept, efficient in computation, and robust and flexible in modeling the human evaluation process, thus making it of general use for solving practical MA problems.
Abstract
Presents an approach for solving qualitative multicriteria analysis (MA) problems using fuzzy pairwise comparison. Fuzzy numbers are used to approximate the decision-maker's (DM's) subjective assessments in assessing alternative performance and criteria importance. The concept of fuzzy extent analysis is applied for solving the reciprocal judgement matrices. To avoid the complex and unreliable process of comparing fuzzy utilities, the /spl alpha/-cut technique is applied to transform the fuzzy performance matrix into an interval matrix. Incorporated with the DM's attitude towards risk, an overall performance index is obtained for each alternative across all criteria in line with the ideal solution concept. An empirical study of a tender selection problem in Australia is conducted. The result shows that the approach developed is simple and comprehensible in concept, efficient in computation, and robust and flexible in modeling the human evaluation process, thus making it of general use for solving practical MA problems.

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Citations
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Journal ArticleDOI

Deriving priorities from fuzzy pairwise comparison judgements

TL;DR: A new approach for deriving priorities from fuzzy pairwise comparison judgements is proposed, based on α-cuts decomposition of the fuzzy judgements into a series of interval comparisons, which requires the solution of a non-linear optimisation program.
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Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology

TL;DR: In this paper, a two step methodology is structured to evaluate hazardous waste transportation firms containing the methods of fuzzy-AHP and TOPSIS.
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Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods

TL;DR: A fuzzy model to evaluate the performance of the firms by using financial ratios and at the same time, taking subjective judgments of decision makers into consideration is developed.
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Evaluation of Services Using a Fuzzy Analytic Hierarchy Process

TL;DR: The proposed fuzzy prioritisation method uses fuzzy pairwise comparison judgements rather than exact numerical values of the comparison ratios and transforms the initial fuzzy prioritisations problem into a non-linear program, which eliminates the need of additional aggregation and ranking procedures.
Journal ArticleDOI

Fuzzy Multicriteria Decision-Making: A Literature Review

TL;DR: This paper surveys the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision- Making (MADM) and fuzzy multiobjective decision- making (MODM).
References
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Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book ChapterDOI

The Analytic Hierarchy Process

TL;DR: Analytic Hierarchy Process (AHP) as mentioned in this paper is a systematic procedure for representing the elements of any problem hierarchically, which organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pairwise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy.
Book

Multiple Attribute Decision Making: Methods and Applications

TL;DR: In this paper, the authors present a classification of MADM methods by data type and propose a ranking method based on the degree of similarity of the MADM method to the original MADM algorithm.
Journal ArticleDOI

Applications of the extent analysis method on fuzzy AHP

TL;DR: The use of triangular fuzzy numbers for pairwise comprison scale of fuzzy AHP is introduced, and the use of the extent analysis method for the synthetic extent value S i of the pairwise comparison is used.
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