Green Vehicle Routing Problem (GVRP) addresses the primary sources of carbon emissions, which is distribution. This paper aims to fulfill the demand for a set of customers using a fleet of vehicles originating from a single depot with the primary objective of minimizing carbon dioxide equivalent emissions. This work defines a mixed-integer linear programming model that considers heterogeneous vehicles, customer time window constraints, service time at each customer, and vehicle capacity constraints in GVRP. The model is studied on a real-life case study using three objectives functions; the classical vehicle routing problem objective of minimizing the total travel distance, minimizing the deviation of a fleet of vehicles’ traveling speed from the optimum traveling speed, and directly minimizing the total amount of emissions produced. This work also studies the effect of varying vehicle velocity and distance on the amount of emissions produced. The computational results show that up to 9% and 21% reduction in emissions and fuel consumption can be achieved compared to distance-oriented solutions and velocity oriented solutions, respectively.