Abstract
AbstractThis article elaborates on the connection between multiple criteria decision aiding (MCDA) and preference learning (PL), two research fields with different roots and developed in different communities. It complements the first part of the paper, in which we started with a review of MCDA. In this part, a similar review will be given for PL, followed by a systematic comparison of both methodologies, as well as an overview of existing work on combining PL and MCDA. Our main goal is to stimulate further research at the junction of these two methodologies.
Funder
Ludwig-Maximilians-Universität München
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Theoretical Computer Science,Management Information Systems,Management Science and Operations Research