When using a constructive search algorithm, solutions to scheduling problems such as the job shop and open shop scheduling problems are typically represented as permutations of the operations to be scheduled. The combination of this representation and the use of a constructive algorithm introduces a bias typically favouring good solutions. When ant colony optimisation is applied to these problems, a number of alternative pheromone representations are available, each of which interacts with this underlying bias in different ways. This paper explores both the structural aspects of the problem that introduce this underlying bias and the ways two pheromone representations may either lead towards poorer or better solutions over time. Thus it is a synthesis of a number of recent studies in this area that deal with each of these aspects independently.
History
Publication title
Proceedings of the 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2005)
Volume
3533
Editors
M Ali, F Esposito
Pagination
218-228
ISBN
978-3-540-26551-1
Department/School
School of Information and Communication Technology
Publisher
Springer-Verlag
Place of publication
Berlin
Event title
18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2005)
Event Venue
Bari, Italy
Date of Event (Start Date)
2005-06-22
Date of Event (End Date)
2005-06-24
Rights statement
Copyright 2005 Springer-Verlag Berlin Heidelberg
Repository Status
Open
Socio-economic Objectives
Expanding knowledge in the information and computing sciences