A GRASP embedded Scatter Search is developed for the multicommodity capacitated network design problem. Difficulty for this problem arises from the fact that selection of the optimal network design is an NP-complete combinatorial problem. There exist no polynomial exact algorithms which can solve this problem in a reasonable period of time for realistically sized instances. In such cases, heuristic procedures are commonly used. Two strategies were designed for GRASP: a traditional approach and a memory based technique. As for Scatter Search, 5 different strategies were used to update the reference set. Computational results on a large set of randomly generated instances show the convenience of the proposed procedures.

A fixed charge capacitated multicommodity network design problem on undirected networks is addressed. At the present time, there exists no algorithm that can solve large instances, common in several applications, in a reasonable period of time. This paper presents an efficient procedure using a scatter search framework. Computational experiments on a large set of randomly generated problems show that this procedure is capable of finding good solutions to large-scale problems within a reasonable amount of time.