A VARIABLE-DEPTH NEIGHBORHOOD SEARCH ALGORITHM FOR THE VEHICLE ROUTING PROBLEM WITH SIMULTANEOUS PICKUPS AND DELIVERIES

We address the Vehicle Routing Problem with Simultaneous Pickups and Deliveries by means of a Variable Depth Neighborhood Search algorithm. This problem has applications in areas with significant economic, social, and environmental impact, such as reverse logistics, recycling, and waste management. In this context, distribution and collection operations need to be considered together to minimize logistical efforts. A new Integer Linear Programming formulation is proposed for the problem version with a heterogeneous fleet. We propose a hybrid method with a variable depth neighborhood structure explored through the resolution of an ILP model, similar to other hybridizations based on problem instance reduction. The results of the computational experiments are promising, yielding new upper and lower bounds for instances from the literature.