Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
482309 | European Journal of Operational Research | 2007 | 10 Pages |
Abstract
This paper presents ACO_GLS, a hybrid ant colony optimization approach coupled with a guided local search, applied to a layout problem. ACO_GLS is applied to an industrial case, in a train maintenance facility of the French railway system (SNCF). Results show that an improvement of near 20% is achieved with respect to the actual layout. Since the problem is modeled as a quadratic assignment problem (QAP), we compared our approach with some of the best heuristics available for this problem. Experimental results show that ACO_GLS performs better for small instances, while its performance is still satisfactory for large instances.
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Authors
Y. Hani, L. Amodeo, F. Yalaoui, H. Chen,