  We propose a metaheuristic algorithm enhanced with feature-based guidance
that is designed to solve the Capacitated Vehicle Routing Problem (CVRP). To
formulate the proposed guidance, we developed and explained a supervised
Machine Learning (ML) model, that is used to formulate the guidance and control
the diversity of the solution during the optimization process. We propose a
metaheuristic algorithm combining neighborhood search and a novel mechanism of
hybrid split and path relinking to implement the proposed guidance. The
proposed guidance has proven to give a statistically significant improvement to
the proposed metaheuristic algorithm when solving CVRP. Moreover, the proposed
guided metaheuristic is also capable of producing competitive solutions among
state-of-the-art metaheuristic algorithms.
