A fuzzy approach to deriving priorities from interval pairwise comparison judgements

Mikhailov, Ludmil

doi:10.1016/s0377-2217(03)00432-6

Cited by 171 publications

(76 citation statements)

References 33 publications

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“…Nevertheless, Hauser and Tadukamalla (1996) pointed out that, most of DMs' judgments in an interval would converge to a fixed value which is usually the center of the interval. Mikhailov (2004) and Chen and Xu (2015) also supported the view that the center of the interval is the most possible judgment of DM in an IVFPR.…”

Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 52%

“…It takes the constraints of priority weights as fuzzy constraints and constructs the membership functions of fuzzy constraints to express DM's satisfaction. By maximizing DM's satisfaction degree, the fuzzy program is established to determine the priority weights from IVMPR (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015).…”

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

“…The above membership function is often employed in the FPM to derive the priority weights from an IVMPR (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015). However, there exist some shortcomings when using Eq.…”

Section: Letmentioning

confidence: 99%

“…(b) Many studies (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015) applied the convex probability distribution in probabilistic methods to fuzzy/multiplicative preference relation. Especially, the triangular or trapezoidal fuzzy judgments are usually employed in the FPMs (Mikhailov 2002(Mikhailov , 2003(Mikhailov , 2004Chen and Xu 2015).…”

Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 99%

“…Mikhailov (2003) transformed the interval prioritization task into a fuzzy linear programming problem for deriving optimal crisp priorities from an IVMPR. By transforming interval judgments into fuzzy inequality constraints, Mikhailov (2004) established linear or non-linear membership functions to represent DMs' satisfaction degree. Subsequently, Chen and Xu (2015) proposed a novel FPM to derive the priority vectors.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Wan

Wang

et al. 2016

Fuzzy Optim Decis Making

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Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 52%

Section: Shortcomings Of the Fpm For Deriving The Priority Weights Frmentioning

confidence: 99%

Section: Letmentioning

confidence: 99%

Section: Approaches To Solving the Constructed Intuitionistic Fuzzy Pmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Wan

Wang

et al. 2016

Fuzzy Optim Decis Making

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Project risk evaluation using a fuzzy analytic hierarchy process: An application to information technology projects

Tüysüz

Kahraman

2006

Int. J. Intell. Syst.

104

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Projects are critical to the realization of performing organization's strategies. Each project contains some degree of risk and it is required to be aware of these risks and to develop the necessary responses to get the desired level of project success. Because projects' risks are multidimensional, they must be evaluated by using multi-attribute decision-making methods. The aim of this article is to provide an analytic tool to evaluate the project risks under incomplete and vague information. The fuzzy analytic hierarchy process~AHP! as a suitable and practical way of evaluating project risks based on the heuristic knowledge of experts is used to evaluate the riskiness of an information technology~IT! project of a Turkish firm. The means of the triangular fuzzy numbers produced by the IT experts for each comparison are successfully used in the pairwise comparison matrices.

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A comprehensive uncertainty analysis of the analytic hierarchy process methodology applied in the context of environmental decision making

Toth

Vacik

2018

Multi Criteria Decision Anal

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An overview of uncertainty issues associated with the analytic hierarchy process (AHP) is provided. Further, an explicit understanding of uncertainty (designation, categorization, and quantification) with respect to the methodological properties of the AHP is developed and used to analyse a hypothetical group decision problem located in the context of environmental decision making (EDM). To calculate the numerical impact of especially designed uncertainty scenarios (USs) on the final ranking given by the AHP, a simulation experiment is conducted using R. It evaluates the impact of uncertainty within three variants of a hypothetical decision-making case by calculating an "overall uncertainty" measure. The consideration of uncertainty may lead to a rank reversal in comparison with that analysis neglecting uncertainty (best alternative given by the AHP). The results show that the absolute maximal impact caused by a US is approximately 0.03. With respect to a single US and the specific case characteristics, in about 50% of the simulated runs a rank reversal occurs. Similar shares of rank reversal over different USs within a single variant of the case raise the question to which uncertainty should be given prior attention in decision-making practice. For decision analysts in EDM, this result implies that additional resources may be necessary to commonly negotiate with decision makers that uncertainties should be addressed. From a theoretical normative point of view, the effects of considering uncertainty issues in the AHP methodology cannot satisfy the ideal of a rational decision analysis. From a descriptive point of view, considering the practice of decision makers, the impacts of the considered uncertainties stay within reasonable limits, meaning that the maximal numerical impact stays on the hundredths decimal place. KEYWORDS designation, categorization, and quantification of uncertainty, overall uncertainty measure, scenarios, simulation experiment, uncertainty modellingThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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A fuzzy approach to deriving priorities from interval pairwise comparison judgements

Cited by 171 publications

References 33 publications

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

An intuitionistic fuzzy programming method for group decision making with interval-valued fuzzy preference relations

Project risk evaluation using a fuzzy analytic hierarchy process: An application to information technology projects

A comprehensive uncertainty analysis of the analytic hierarchy process methodology applied in the context of environmental decision making

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