Ant colony optimization for solving an industrial layout problem

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. (c) 2006 Elsevier B.V. All rights reserved.