Rotation Invariance and Rotated Problems: An Experimental Study on Differential Evolution

Date

2018-03-08

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Springer

Type

Conference

Peer reviewed

Yes

Abstract

This paper presents an experimental study on the efficacy of a rotation-invariant Differential Evolution (based on current-to-rand mutation) on a benchmark of test problems in its non-rotated and rotated version. Numerical results show that standard Differential Evolution outperforms rotation-invariant Differential Evolution on the benchmark under consideration for both non-rotated and rotated problems. In other words, the rotation-invariant Differential Evolution does not seem to be more efficient than its standard counterpart to address rotated problems. According to our interpretation, these experimental results show that rotated problems are simply different problems with respect to the non-rotated problems. Furthermore, rotation-invariant Differential Evolution is characterised by its moving operator: it generates an offspring by perturbing all the design variables of a candidate solution at the same time. This logic does not appear to guarantee a better performance on rotated problems.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link

Keywords

Differential Evolution, Rotational Invariant Algorithms, Separability, Epistasis, Continuous Optimisation

Citation

Caraffini, F. and Neri, F. (2018) Rotation Invariance and Rotated Problems: An Experimental Study on Differential Evolution. In: Sim, K. et al. (eds.), proceedings of Applications of Evolutionary Computation - 21st International Conference EvoApplications 2018, Parma, April 2018. Lecture Notes in Computer Science, 10784, Berlin: Springer, pp. 597-614.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)