Methodologies and Algorithms for Group-Rankings Decision

The problem of group ranking, a.k.a. rank aggregation, has been studied in contexts varying from sports, to multi-criteria decision making, to machine learning, to ranking web pages, and to behavioral issues. The dynamics of the group aggregation of individual decisions has been a subject of central importance in decision theory. We present here a new paradigm using an optimization framework that addresses major shortcomings that exist in current models of group ranking. Moreover, the framework provides a specific performance measure for the quality of the aggregate ranking as per its deviations from the individual decision makers' rankings. The new model for the group ranking problem presented here is based on rankings provided with intensity

• Type: Journal
• Year: 2006
• Where: MANSCI
• Authors: Dorit S. Hochbaum, Asaf Levin
• Keywords: Group, Individual Decision, MANSCI 2006, Rankings