Method for Computing Optimal Consensus Rankings

A method, apparatus, and program product are provided for ranking a plurality of items. A plurality of items is received. Criteria associated with the plurality of items and weights associated with each criterion are defined. Intermediate rankings are either generated using at least one sorting algorithm or provided or both. A conformity matrix and scoring function are generated from the intermediate rankings. A customized genetic algorithm seeks a ranking that maximizes the scoring function by evolving a population of rankings according to each ranking's unsolved ranges. An unsolved range in a ranking is identified based on the conformity matrix and scoring function. In response to a ranking having additional unsolved ranges, the steps of identifying the unsolved range and rearranging the items using the customized genetic algorithm are repeated. In response a ranking have no additional unsolved ranges, the ranking for the plurality of items is provided.