PROMETHEE

Abstract

PROMETHEE (preference ranking organization method for enrichment evaluation) introduced in Brans, Mareschal, and Vincke (1984) and Brans, Vincke, and Mareschal (1986), is a multi-criteria decision support tool for the ranking of alternatives based on their values over different criteria. As an outranking method, it quantifies a ranking through the pairwise preference comparison (differences) between the criterion values describing the alternatives. The main initial goal of PROMETHEE was to offer a means of multi-criteria decision support characterised by simplicity and clearness to the decision maker (Brans et al., 1986). PROMETHEE is also considered to have a transparent computational procedure (Georgopoulou, Sarafidis, & Diakoulaki, 1998). These characteristics of PROMETHEE have made it a versatile methodology in many areas of study, including in particular energy management (Pohekar & Ramachandran, 2004; Simon, Brüggemann, & Pudenz, 2004), but also more diverse areas such as decision making in stock trading (Albadvi, Chaharsooghi, & Esfahanipour, 2006) and authentication of food products (Zhang, Ni, Churchill, & Kokot, 2006). Developments on the original PROMETHEE include: an interval version (Le Téno & Mareschal, 1998), a fuzzy version (Radojevic & Petrovic, 1997), and a stochastic version (Marinoni, 2005), as well as its utilisation to elucidate rank uncertainty (Hyde, Maier, & Colby, 2003). These developments have been undertaken to take into account the possible imprecision and distribution of the concomitant criteria values considered. The graphical bi-plot representation called GAIA (geometrical analysis for interactive aid), based on a special type of principal component analysis, was developed to identify the principal criteria that contribute to the rank order of the alternatives when using PROMETHEE (Keller, Massart, & Brans, 1991). Recently, the use of constellation plots has also enabled a visual representation of the preference contribution of the criteria (Beynon, 2008). Concerns and consequences on the use of PROMETHEE were succinctly outlined in De Keyser and Peeters (1996), including how the importance weights of criteria should be interpreted and the effect of adding or deleting an alternative from consideration. A small example data set of alternatives is considered here to illustrate the operational rudiments of PROMETHEE. The acknowledgement of uncertainty in an identified ranking, when employing PROMETHEE, is also demonstrated, using the approach of Hyde et al. (2003) and Hyde and Maier (2006).