A Hybrid Metaheuristic to Solve Capacitated Vehicle Routing Problem

Many real life problems that play a major role in human lives are mostly optimization problems and need to be solved in order to judiciously utilize vital resources. The vast solution space consists of a large number of feasible solutions. Solving these problems requires finding the most optimal solution while satisfying the constraints imposed (if any). Vehicle Routing is a real life problem originated primarily in the logistics industry where the consignments are to be delivered to the clients in such a way, that there is minimal usage of resources like fuel, and time. In addition, the consignments are to be successfully delivered to the clients through the shortest route and utilizing the maximum capacity of each vehicle. Automation is the key to solve such large problems while reducing effort and complexity of the solution. Literature reveals that nature inspired algorithms have proved their ability for solving such large complex optimization problems. These algorithms are inspired from various natural phenomena and are supported by their successful survival. This paper proposes a hybrid framework to solve Vehicle Routing Problem (VRP) utilizing Differential Evolution and Marine Predators algorithm. We have considered the variant called Capacitated Vehicle Routing Problem (CVRP) to conduct experiments and compared the results to evaluate the performance of proposed hybrid approach DEMPA with Differential Evolution (DE). Results indicate the superiority of the proposed approach over Differential Evolution.