Group Aggregation of Pairwise Comparisons using Multi-Objective Optimization

Edward Abel, L. Mikhailov, J Keane

Research output: Contribution to journalArticlepeer-review

153 Downloads (Pure)

Abstract

In group decision making, multiple decision makers (DMs) aim to reach a consensus ranking of alternatives in a decision problem. The differing expertise, experience and, potentially conflicting, interests of the DMs will result in the need for some form of conciliation to achieve consensus. Pairwise comparisons are commonly used to elicit values of preference of a DM. The aggregation of the preferences of multiple DMs must additionally consider potential conflict between DMs and how these conflicts may result in a need for compromise to reach group consensus. We present an approach to aggregating the preferences of multiple DMs, utilizing multi-objective optimization, to derive and highlight underlying conflict between the DMs when seeking to achieve consensus. Extracting knowledge of conflict facilitates both traceability and transparency of the trade-offs involved when reaching a group consensus. Further, the approach incorporates inconsistency reduction during the aggregation process to seek to diminish adverse effects upon decision outcomes. The approach can determine a single final solution based on either global compromise information or through utilizing weights of importance of the DMs. Within multi-criteria decision making, we present a case study within the Analytical Hierarchy Process from which we derive a richer final ranking of the decision alternatives.
Original languageEnglish
Pages (from-to)257-275
Number of pages18
JournalInformation Sciences
Volume322
Issue number20
DOIs
Publication statusPublished - Nov 2015

Keywords

  • Group decision making;
  • Multi-criteria decision making
  • Multi-objective optimization

Fingerprint

Dive into the research topics of 'Group Aggregation of Pairwise Comparisons using Multi-Objective Optimization'. Together they form a unique fingerprint.

Cite this