A mathematical model for many-to-many hub location-routing problem with various capacity decisions and constrained distance length : Meta-heuristic algorithms

Hub location-routing problem is typically a new and practical subject in the last decades. In this paper, a mathematical model for the hub location-routing problem is proposed, which considers miscellaneous capacity constraints for the hubs. To find practical solutions, transportation fleet have constrained capacity and also distance length of vehicle tour is restricted. What is more, the balancing requisites are imposed on the network by allocating the appropriate number of demand nodes to the hubs. Moreover, two meta-heuristic algorithms, including Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA) are employed to solve the proposed model. Finally, a number of numerical examples are also investigated, in an attempt to demonstrate the validity of the proposed mathematical model and solution approaches. The obtained computational results reveal that GA performance is better than ICA.