SOLVING THE CAPACITATED VEHICLE ROUTING PROBLEM WITH GENETIC ALGORITHMS AND PARALLELISM

Vehicle routing problems (VRP) are classics of combinatorial optimization that are highly applicable in the real world, dealing with the definition of routes for customers and demands in typically restrictive situations. In this work, we propose an approach based on Genetic Algorithms for solving the CVRP, improving it by using the island model, exploiting multithreading and shared memory. An algorithm was implemented and benchmarks were used to explore it. The results showed an improvement in the quality of the solutions and a reduction in variance as more islands were added. The proposed method proved promising for scenarios where conventional solutions encounter limitations. It stands out as an alternative due to the horizontal scalability of computing resources.