We present a vehicle routing problem with load capacity and time windows for a fleet of electric vehicles (EVs) and internal combustion vehicles (ICVs). Different charging technologies, including Level 1, 2, and 3 chargers and swapping batteries, are considered in this research. Given the location of the depot, the existing customers, and the set of charging stations, this problem aims to minimise the overall cost of constructing the routes over the vertices that need to be visited by either an ICV or EV. We develop a mixed-integer linear programming (MILP) model for this problem, and we solve small samples using a CPLEX solver. In addition, we develop two metaheuristic solution approaches by combining Adaptive Large Neighbourhood Search (ALNS) with Simulated Annealing (SA) and Tabu Search (TS). Using a set of locations from Scarborough, Ontario, Canada, we investigate the delivery routing problem with a fleet of ICVs and EVs. By solving the problem for different scenarios, we observed that EVs often require partial recharging and faster chargers (Level 3) when traveling in the city.