Multiple criteria classification with an application in water resources planning

Authors:
Ye Chen;D. Marc Kilgour;Keith W. Hipel
Affiliations:
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada;Department of Mathematics, Wilfrid Laurier University, Waterloo, Ont., Canada;Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada
Venue:
Computers and Operations Research
Year:
2006

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Abstract

A new kind of multiple criteria decision aid (MCDA) problem, multiple criteria classification (MCC), is studied in this paper. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCC is the classification of alternatives into nominal groups, structured by the decision maker (DM), who specifies multiple characteristics for each group. Starting with illustrative examples, the features, definition and structures of MCC are presented, emphasizing criterion and alternative flexibility. Then an analysis procedure is proposed to solve MCC problems systematically. Assuming additive value functions, an optimization model with constraints that incorporate various classification strategies is constructed to solve MCC problems. An application of MCC in water resources planning is carried out and some future extensions are suggested.