HBRKGA Evolutionary Algorithm for Vehicle Routing Problem with Trucks and Drones

Faced with the need for more efficient solutions to the Vehicle Routing Problem (PRV), the Hybrid Vehicle Routing Problem with Trucks and Drones (PRVHCD) stands out, in which trucks and drones act cooperatively, exploring the complementarity between capacity, range, and agility. This work proposes an approach based on Hybrid Biased Random-Key Genetic Algorithm (HBRKGA), with customized encoders and decoders, capable of generating high-quality solutions in feasible computational times. The method was evaluated in instances of the Agatz family, widely used in the literature. The results indicate good performance and versatility of the approach, with competitive solutions, especially in minimizing service time, evidencing its robustness in solving the PRVHCD.