A Bee Colony Optimization Approach for the Electric Vehicle Routing Problem with Drones.

In recent years, studies of vehicle routing problems utilizing novel means of transportation, such as electric ground vehicles and unmanned aerial vehicles, also known as drones, have been increasing in popularity. This paper presents a Bee Colony Optimization (BCO) approach for the recently introduced Electric Vehicle Routing Problem with Drones (EVRPD). The EVRPD utilizes electric vans as mother-ships, from which drones are deployed in order to perform the last-mile delivery to customers. The objective of the EVRPD is to minimize the total energy consumption of the operation and it considers packages of various weights. The Bee Colony Optimization algorithm is one of the few swarm intelligence algorithms designed particularly for solving combinatorial optimization problems. In this approach the exploratory properties of the BCO swarm are combined with the strong exploitative capabilities of the Variable Neighborhood Descent, used as a local search procedure. The results are compared with the other algorithmic approaches in the literature.