Container movement by trucks in metropolitan networks: modeling and optimization

Container movement by trucks with time constraints at origins and destinations is modeled as an asymmetric "multi-Traveling Salesmen Problem with Time Windows" (m-TSPTW) with social constraints. A two-phase exact algorithm based on dynamic programming (DP) is proposed that finds the best routes for a fleet of trucks. Since the m-TSPTW problem is NP-hard, the computational time for optimally solving large size problems becomes prohibitive. For large size problems, we develop a hybrid methodology consisting of DP in conjunction with genetic algorithms. The developed algorithms are compared with an insertion heuristic method. Computational results demonstrate the efficiency of the developed algorithms.