A comparison of heuristics for the discrete cost multicommodity network optimization problem

In this paper, approximate solutions algorithms for discrete cost multicommodity network optimization problems are presented and compared. Firstly, extensions of classical greedy heuristics, based on link-rerouting and flow-rerouting heuristics, are presented in details. Secondly, a new approximate solution algorithm, which basically consists of a heuristic implementation of the exact Benders-type cutting plane generation method, is proposed. All these algorithms are extensively compared on randomly generated graphs up to 50 nodes and 90 links. It clearly appears that this new Benders-type approach is very promising since it produces the best heuristic solutions.