Abstract
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.
Original language | English |
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Title of host publication | Innovations in Applied Artificial Intelligence |
Editors | M Ali, F Esposito |
Publisher | Springer |
Pages | 218-228 |
Number of pages | 11 |
ISBN (Print) | 3-540-26551-1 |
DOIs | |
Publication status | Published - 2005 |
Event | 18th International Industrial and Engineering Applications of Artificial Intelligence and Expert Systems - Bari, Italy Duration: 22 Jun 2005 → 24 Jun 2005 Conference number: 18 |
Publication series
Name | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
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Publisher | SPRINGER-VERLAG BERLIN |
Volume | 3533 |
ISSN (Print) | 0302-9743 |
Conference
Conference | 18th International Industrial and Engineering Applications of Artificial Intelligence and Expert Systems |
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Abbreviated title | IEA/AIE |
Country/Territory | Italy |
City | Bari |
Period | 22/06/05 → 24/06/05 |