 Coupling ant colony systems with strong local searchesL.M. Gambardella, R. Montemanni and D. Weyland European Journal of Operational Research, 2012, vol. 220, issue 3, 831-843 Abstract: Ant colony system is a well known metaheuristic framework, and many efficient algorithms for different combinatorial optimization problems have been derived from this general framework. In this paper some directions for improving the original framework when a strong local search routine is available, are identified. In particular, some modifications able to speed up the method and make it competitive on large problem instances, on which the original framework tends to be weaker, are described. The resulting framework, called Enhanced Ant Colony System is tested on three well-known combinatorial optimization problems arising in the transportation field. Many new best known solutions are retrieved for the benchmarks available for these optimization problems. Keywords: Combinatorial optimization; Metaheuristics; Ant colony optimization; Sequential ordering problems; Team orienteering problems; Probabilistic traveling salesman problems (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:220:y:2012:i:3:p:831-843 DOI: 10.1016/j.ejor.2012.02.038 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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