Minimal sets of quality metrics

Authors:
A. Farhang-Mehr;S. Azarm
Affiliations:
Department of Mechanical Engineering, University of Maryland, College Park, Maryland;Department of Mechanical Engineering, University of Maryland, College Park, Maryland
Venue:
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Year:
2003

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Abstract

Numerous quality assessment metrics have been developed by researchers to compare the performance of different multi-objective evolutionary algorithms. These metrics show different properties and address various aspects of solution set quality. In this paper, we propose a conceptual framework for selection of a handful of these metrics such that all desired aspects of quality are addressed with minimum or no redundancy. Indeed, we prove that such sets of metrics, referred to as 'minimal sets', must be constructed based on a one-to-one correspondence with those aspects of quality that are desirable to a decision-maker.