Authors: Dimitri Van Assche; Yves De Smet
Addresses: Computer and Decision Engineering (CoDE), SMG Research Unit, Université libre de Bruxelles, Avenue Franklin D. Roosevelt 50, CP 210/01, B-1050 Brussels, Belgium ' Computer and Decision Engineering (CoDE), SMG Research Unit, Université libre de Bruxelles, Avenue Franklin D. Roosevelt 50, CP 210/01, B-1050 Brussels, Belgium
Abstract: In multi-criteria sorting methods, it is often difficult for decision makers to precisely define their preferences. It is even harder to express them into parameters values. The idea of this work is to automatically find the parameters of a sorting model using classification examples in the contexts of traditional sorting and interval sorting. Interval sorting, i.e., the possible assignment of alternatives into several successive categories, is defined in this paper. The sorting method we are working with is FlowSort, which is based on the PROMETHEE methodology. Starting with an evaluation table and known allocations, we propose a heuristic based on a genetic algorithm (GA) to identify the weights, indifference and preference thresholds but also profiles characterising the categories. We illustrate both the performances of the algorithm and the quality of the solutions on three standard datasets in both cases.
Keywords: preference learning; PROMETHEE; FlowSort parameters; interval sorting; genetic algorithms; categorisation; multicriteria sorting; preferences; classification.
International Journal of Multicriteria Decision Making, 2016 Vol.6 No.3, pp.191 - 210
Received: 30 Mar 2015
Accepted: 25 Feb 2016
Published online: 07 Oct 2016 *