Skip to content

Learning to make intelligent decisions using an Expert System for the intelligent selection of either PROMETHEE II or the Analytical Hierarchy Process

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

This paper presents an expert system to select a most suitable discrete Multi Criteria Decision Making (MCDM) method using an approach that analyses problem characteristics, MCDM methods characteristics, risk and uncertainty in inputs and applies sensitivity analysis to the inputs for a decisional problem. Outcomes of this approach can provide decision makers with a suggested candidate method that delivers a robust outcome. Numerical examples are presented where two MCDM methods are compared and one is recommended by calculating the minimum percentage change in criteria weights and performance measures required to alter the ranking of any two alternatives. A MCDM method will be recommended based on a best compromise in minimum percentage change required in inputs to alter the ranking of alternatives.
Original languageEnglish
Title of host publicationIntelligent Systems and Applications
Subtitle of host publicationProceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer
Pages1303-1316
ISBN (Electronic)978-3-030-01054-6
ISBN (Print)978-3-030-01053-9
DOIs
Publication statusPublished - Jan 2019
EventIntelliSys 2018 - London, United Kingdom
Duration: 6 Sep 20187 Sep 2018

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume868
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceIntelliSys 2018
CountryUnited Kingdom
CityLondon
Period6/09/187/09/18

Documents

  • Final_Paper_Malik_IntelliSys_2018_Learning_to_make

    Rights statement: The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-01054-6_91.

    Accepted author manuscript (Post-print), 1.67 MB, PDF document

    Licence: Unspecified

Related information

Activities

Relations Get citation (various referencing formats)

ID: 8212983