Abstract:
An entropy-based metric is presented to assess the diversity of solutions in a multi-objective optimization technique. This metric quantifies the 'goodness' of a solution...Show MoreMetadata
Abstract:
An entropy-based metric is presented to assess the diversity of solutions in a multi-objective optimization technique. This metric quantifies the 'goodness' of a solution set in terms of its distribution quality over the Pareto-optimal frontier. As a demonstration via a three-objective test example, the entropy metric is used as a means of comparing two multi-objective genetic algorithms.
Published in: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)
Date of Conference: 12-17 May 2002
Date Added to IEEE Xplore: 07 August 2002
Print ISBN:0-7803-7282-4
Contents 