Intelligent Collaborative Support System for AHP-Group Decision Making | Zendy

Gang Kou | Zendy; Xiangrui Chao | Zendy; Yi Peng | Zendy; Liang Xu | Zendy; Yang Chen | Zendy

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Intelligent Collaborative Support System for AHP-Group Decision Making

Author(s) -

Gang Kou,

Xiangrui Chao,

Yi Peng,

Liang Xu,

Yang Chen

Publication year - 2017

Publication title -

studies in informatics and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.321

H-Index - 22

eISSN - 1841-429X

pISSN - 1220-1766

DOI - 10.24846/v26i2y201701

Subject(s) - computer science , analytic hierarchy process , group decision making , group (periodic table) , decision support system , r cast , knowledge management , operations research , artificial intelligence , business decision mapping , psychology , social psychology , chemistry , organic chemistry , engineering

The analytic hierarchy process (AHP) was originally proposed by Saaty (1977, 1980, 1986) and is widely applied in decision making and management practice. The procedure obtains priorities based on multiple actors, scenarios, and criteria. The AHP is also frequently used in group decision making (GDM), which employs the AHP to answer group decision making questions due to its simplicity, power, and compatibility (Saaty 1989). For the AHP-GDM, each decision maker provides an individual pair-wise comparison matrix (PCM) in every local context of the hierarchy, and then several aggregation approaches are applied to obtain the group preference from the individual pairwise comparison matrices. The decisionmaking procedure in the AHP-GDM can be divided into 3 stages (Chiclana 2008, Dong et al. 2015): priority vector derivation, preference aggregation, and consensus reaching.

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