Ant colony optimisation applied to a dynamically changing problem

Search Swinburne Research Bank

Home

Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/4119

Title: Ant colony optimisation applied to a dynamically changing problem
Author(s): Angus, Daniel; Hendtlass, Tim
Abstract: Ant Colony optimisation has proved suitable to solve static optimisation problems, that is problems that do not change with time. However in the real world changing circumstances may mean that a previously optimum solution becomes suboptimial. This paper explores the ability of the ant colony optimisation algorithm to adapt from the optimum solution to one set of circumstances to the optimal solution to another set of circumstances. Results are given for a preliminary investigation based on the classical travelling salesperson problem. It is concluded that, for this problem at least, the time taken for the solution adaption process is far shorter than the time taken to find the second optimum solution if the whole process is started over from scratch.
Publication type: Conference paper
Research centre: Swinburne University of Technology. School of Biophysical Sciences and Electrical Engineering
Source: 15th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 02), Cairns, Queensland, Australia, 17-20 June 2002, Vol. 2358, pp. 618-627
Publication year: 2002
Publisher: Springer-Verlag
Publisher URL: http://dx.doi.org/10.1007/3-540-48035-8_60
Peer reviewed