Title: A multicriteria ordered clustering algorithm to determine precise or disjunctive partitions
Authors: Mohamed Ayman Boujelben; Yves De Smet
Addresses: MODEOR, Institut des hautes études commerciales, Université de Sfax, Route Sidi Mansour, BP 967, 3018 Sfax, Tunisie ' CoDE-SMG, Ecole polytechnique de Bruxelles, Université libre de Bruxelles, Boulevard du Triomphe, CP 210-01, 1050 Bruxelles, Belgique
Abstract: We consider multicriteria clustering problems where the groups are ordered from the best to the worst. An approach relying on the principles of the k-means algorithm and disjunctive sorting based on evidence theory (DISSET) method is proposed for the detection of ordered clusters. The distinctive feature of this method is that it allows to obtain both precise and disjunctive partitions. In such situation, the actions can be assigned even to pair of groups (and not only to precise clusters). The decision maker is assumed to provide the following inputs: an evaluation table, the desired number of clusters and a valued preference model (obtained for instance by PROMETHEE method). The method is illustrated on two real examples: the Human Development Index (HDI-2013) and the Logistics Performance Index (LPI-2014).
Keywords: multicriteria decision aiding; MCDA; evidence theory; multicriteria ordered clustering; precise partitions; disjunctive partitions; multicriteria decision making; MCDM; k-means clustering; disjunctive sorting; evidence theory; DISSET; PROMETHEE.
DOI: 10.1504/IJMCDM.2016.077886
International Journal of Multicriteria Decision Making, 2016 Vol.6 No.2, pp.157 - 187
Received: 29 Nov 2015
Accepted: 21 Apr 2016
Published online: 20 Jul 2016 *