A GRASP HEURISTIC FOR THE ACTIVE AND PASSIVE VEHICLE ROUTING PROBLEM

The Active Passive Vehicle Routing Problem (APVRP) arises in relevant logistics operations, requiring coordination between active vehicles, which move autonomously, and passive vehicles, which rely on the active ones for transportation. This work proposes a GRASP (\textit{Greedy Randomized Adaptive Search Procedure}) heuristic to solve it, focusing on large instances where exact methods face scalability limitations. Furthermore, the use of the solutions obtained by GRASP is analyzed as a starting point for solving the problem through a general-purpose mixed-integer programming solver, using an APVRP formulation. To evaluate the approaches, experiments were conducted using benchmark instances from the literature, comparing the performance of GRASP with another heuristic in the literature. The results show that GRASP produces good solutions with low computational time and, when used as an initial solution, improves the solver’s performance.