A GP-AHP method for solving group decision-making fuzzy AHP problems

By Chian-Son Yu. Computers & Operations Research, 2002

343 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Management Science and Operations Research, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/b4c5379ef200550925b98a95daae165fd7b89ee1

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In Control and Systems Engineering

In Management Science and Operations Research

In Organizational Behavior and Human Resource Management

Citations in the corpus

Application and Development of a Fuzzy Analytic Hierarchy Process within a Capital Investment Study (2005, methodology): “It does not require the evaluation of fuzzy eigenvalues (Juang and Lee, 1991) or the solving of a linear programming problem (e.g., in Arbel, 1989; Bryson and Joseph, 1999; Yu, 2002), instead it utilises a number of rows and columns averaged from the associated fuzzy comparison matrices (Beynon and ”
A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan (2008, background): “Conventional AHP that requires the selection of arbitrary values in pairwise comparison may not be sufficient, and uncertainty should be considered in some or all pairwise comparison values (Yu, 2002).”
Analytic hierarchy process: An overview of applications (2006, background): “Management – 17 [138] 1993 Weber S F Manufacturing – 18 [141] 1990 Weiss E N Social Dynamic programming 19 [145] 2003 Xu S Industry – 20 [147] 2002 Yu C S Personal – 21 [149] 1997 Zahedi F M Engineering – O.”
Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology (2009, background): “Conventional AHP that requires the selection of arbitrary values in pairwise comparison may not be sufficient, and uncertainty should be considered in some or all pairwise comparison values (Yu, 2002).”
Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain (2012, background): “This fuzziness and vagueness can be managed by increasing robustness of the model (Yu, 2002).”
Modeling uncertainty in multi-criteria decision analysis (2012, methodology): “[157] use a multi-objective linear programming approach to maximize membership values and minimize inconsistency, requiring an additional trade-off parameter.”
Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company (2014, methodology): “The major limitation of the TOPSIS method lies in the inability to capture the vagueness or ambiguity inherent in the decision making process (Yu, 2002).”
Fuzzy Analytic Hierarchy Process and its Application (2008, methodology): “Yu (2002) incorporates an absolute term linearization technique and a fuzzy rating expression into a GP-AHP model for solving group decision-making fuzzy AHP problem.”
Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers (2018, methodology): “TOPSIS method has some limitations in capturing the vagueness of data under fuzzy environment (Kannan et al., 2014), which Yu (2002) stated that fuzziness and vagueness are characteristics of many decisionmaking problems.”