On the behaviour of extremal optimisation when solving problems with hidden dynamics

Authors:
Irene Moser;Tim Hendtlass
Affiliations:
Centre for Intelligent Systems and Complex Processes, Swinburne University of Technology, Australia;Centre for Intelligent Systems and Complex Processes, Swinburne University of Technology, Australia
Venue:
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Year:
2006

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Abstract

Solving dynamic combinatorial problems poses a particular challenge to optimisation algorithms. Optimising a problem that does not notify the solver when a change has been made is very difficult for most well-known algorithms. Extremal Optimisation is a recent addition to the group of biologically inspired optimisation algorithms. Due to its extremely simple functionality, it is likely that the algorithm can be applied successfully in such a dynamic environment. This document examines the capabilities of Extremal Optimisation to solve a dynamic problem with a large variety of different changes that are not explicitly announced to the solver.