A multi-view approach to multi-criteria decision making
by Francisco J. dos Santos; André L.V. Coelho
International Journal of Information and Decision Sciences (IJIDS), Vol. 15, No. 1, 2023

Abstract: In this paper, we investigate a new approach to multi-criteria decision making (MCDM) centred upon the application of canonical correlation analysis (CCA) to distinct groups of judgement criteria. By resorting to MV-MCDM (multi-view multi-criteria decision making), one can estimate reliable values for criteria weights via CCA for multi-view multi-criteria problems; reduce the dimensionality of the decision matrix by considering only one of the available views; and easily extend well-known MCDM methods, such as simple additive weighting (SAW) and technique for order of preferences by similarity to ideal solution (TOPSIS). MV-MCDM also allows the adoption of different aggregation methods (such as the Choquet integral and a new heuristic based on radar charts) to generate the overall scores of the alternatives. A numerical example with the multi-view versions of SAW and TOPSIS demonstrates the applicability of the novel approach.

Online publication date: Mon, 20-Mar-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Decision Sciences (IJIDS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com