An adapted heuristic approach for a clustered traveling salesman problem with loading constraints

The joint optimization of routing and loading operations is crucial to fully optimize the overall planning process in logistics, and as a result routing problems with side constraints are becoming more and more important during the last years. This paper approaches the design of optimal routes for pickup and delivery operations considering in addition some capacity and loading constraints on the vehicles to be used. It is focused on exploiting new ideas to deal with real life situations in which the customers are not uniformly distributed on the pickup or delivery regions of the problem. An adapted and effective heuristic based on a Variable Neighborhood Search framework using improved neighborhood structures is proposed and discussed. The algorithm is applied to several new sets of instances with special structures to better represent real life situations, providing computational results to evaluate its performance.