Abstract

Diversity is a very important property for non-dominated sets. The diversity is a measure of how much information is contained in a non-dominated set. Evaluating diversity has been a diffcult issue in multi-objective evolutionary computation. Many diversity performance measures fail in simple cases. In this work, we describe the most common problems in diversity performance measures and we propose a more robust approach. The problem with most performance measures is that they consist on evaluating the standard deviation of the distances between the elements of the non-dominated sets, or a similar calculation. This dependence on a standard deviation produces a high sensibility to small changes in the non-dominated sets. Our approach is based on an hype-volume associated to the non-dominated set. The behavior of this hyper-volume is exactly what we expect from a diversity performance measure. We tested our approach using a benchmark published in bibliography, showing an exceptional performance.

Full document

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document
Back to Top

Document information

Published on 01/07/10
Accepted on 01/07/10
Submitted on 01/07/10

Volume 26, Issue 3, 2010
Licence: CC BY-NC-SA license

Document Score

0

Views 1
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?