Validating multiattribute decision making methods for supporting group decisions

Chung Hsing Yeh, Yu Hern Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Different multiattribute decision making (MADM) methods often produce inconsistent ranking outcomes for the same problem. In group decision settings, individual ranking outcomes made by individual decision makers are often inconsistent with the group ranking outcome. To address the inconsistency problem of ranking outcomes, this paper develops a new validation approach for selecting the most valid ranking outcome among all feasible outcomes. Based on four normalization procedures and three aggregation procedures, nine MADM methods are developed to solve the general group MADM problem that requires cardinal ranking of the decision alternatives. The validation approach selects the group ranking outcome of an MADM method which has the highest consistency degree with its corresponding individual ranking outcomes. A scholarship student selection problem is used to illustrate how the approach works. The approach is applicable to large-scale multiattribute group decision problems where inconsistent ranking outcomes often exist between different MADM methods and between different decision makers.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2008
PublisherIEEE Computer Society
Pages878-883
Number of pages6
ISBN (Print)9781424416745
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2008 - Chengdu, China
Duration: 2008 Sept 212008 Sept 24

Publication series

Name2008 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2008

Other

Other2008 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2008
Country/TerritoryChina
CityChengdu
Period08-09-2108-09-24

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering

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