In this study, a bi-objective Green Vehicle Routing Problem (GVRP) is presented as an extension of the well-known Vehicle Routing Problem (VRP). Green Vehicle Routing Problem aims to improve routing decisions of companies using Alternative Fuel Vehicles to reduce carbon emissions. Due to the limited number of Alternative Fuel Stations, alternative fuel vehicles have limited driving distances. Therefore, the routing decisions of alternative fuel vehicles are more critical and difficult. The presented problem herein has two objectives that are the minimization of total carbon emissions and the maximization of service level. While total carbon emission is assumed to be proportional to total distance, cargo delivery time window violations of customers are considered as an indicator of service level. The problem was modeled as Mixed-Integer Linear Programming (MILP) and ε-constraint method, a multi-objective optimization method, is used to solve it. Since this method enumerates all Pareto-optimal solutions of a multi-objective problem, the proposed model presents the best solutions that have different carbon emission and service level values to the decision maker. Our proposed model is tested on six realistically designed hypothetical case studies. Three of the case studies are in the Izmir city while three of the case studies are in the Aegean Region, Turkey. According to the results of this study, the minimization of carbon emission and maximization of service level are two conflicting objectives. As service level increases, the number of vehicles and carbon emissions also increase. As carbon emission increases and time windows violation decreases, more vehicles and alternative fuel stations are used. This shows that increasing service level by decreasing time windows violation requires not only increasing carbon emissions but also increasing total distance and cost. The problem can be solved effectively up to 20 nodes. After 20 nodes, no feasible solution is obtained within the predetermined solution time limit.