Title

Extending population oriented extremal optimisation to permutation problems

Date of this Version

2017

Document Type

Journal Article

Publication Details

Published version

Randall, M. (2017). Extending population oriented extremal optimisation to permutation problems. International Journal of Applied Mathematics and Informatics, 11, 38-43.

Access the journal

© NAUN

ISSN

2074-1278

Abstract

Extremal optimisation in its canonical form is based on the manipulation of a single solution. This solution is changed iteratively by gradually replacing poor components of it so that over time it improves. Many successful evolutionary optimisers are population based, so it appears a reasonable exercise to extend extremal optimisation in this way. Scaling it up to an entire population presents many challenges, and only a few works have examined possible models. In this paper, a recent approach is expanded upon which extends the approach from assignment type problems (such as the generalised assignment problem) to permutation oriented ones. Using the asymmetric travelling salesman problem as a test case, it is found that improvements over a canonical extremal optimisation algorithm were realised.

 

This document has been peer reviewed.