In this thesis, a green mixed fleet vehicle routing problem with realistic energy consumption and partial recharges (GMFVRP-REC-PR) is addressed. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. Realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicles. Partial recharging policy is also included into the problem to approach the real life scenario. The objective of this problem is to minimize total travelled distance and total emission produced by internal combustion vehicles. This is a new variant of problem which is developed from E-VRPTMF (Electric Vehicle Routing Problem with Time Windows and Mixed Fleet) that addresses a mixed fleet of electric and internal combustion vehicles, full recharging policy, and operational cost minimization.
We formulate a mixed integer programming model for GMFVRP-REC-PR. Moreover, an adaptive large neighborhood search in which dynamic programming is embedded to optimally solve the recharging station placement is proposed. The algorithm performs well on the tested instances which are originally used for E-VRPTWMF. Moreover, the emission reduction obtained by solving the GMFVRP-REC-PR is presented in this work.

Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250.
Breunig, U., et al. (2019). The electric two-echelon vehicle routing problem. Computers & Operations Research, 103, 198-210. doi:https://doi.org/10.1016/j.cor.2018.11.005
Bureau of Transportation Statistics. (2018). Freight Shipments by Mode. Retrieved from https://www.bts.gov/topics/freight-transportation/freight-shipments-mode
Center for Climate and Energy Solutions. (2019). U.S. State Greenhouse Gas Emissions Targets. Retrieved from https://www.c2es.org/document/greenhouse-gas-emissions-targets/
Dekker, R., et al. (2012). Operations Research for green logistics – An overview of aspects, issues, contributions and challenges. European Journal of Operational Research, 219(3), 671-679. doi:https://doi.org/10.1016/j.ejor.2011.11.010
Desaulniers, G., et al. (2016). Exact algorithms for electric vehicle-routing problems with time windows. Operations Research, 64(6), 1388-1405.
Erdoğan, S., & Miller-Hooks, E. (2012). A Green Vehicle Routing Problem. Transportation Research Part E: Logistics and Transportation Review, 48(1), 100-114. doi:https://doi.org/10.1016/j.tre.2011.08.001
European Environment Agency. (2018a). Greenhouse gas emissions from transport. Retrieved from https://www.eea.europa.eu/data-and-maps/indicators/transport-emissions-of-greenhouse-gases/transport-emissions-of-greenhouse-gases-11
European Environment Agency. (2018b). Transport greenhouse gas emissions. Retrieved from https://www.eea.europa.eu/airs/2018/resource-efficiency-and-low-carbon-economy/transport-ghg-emissions
Felipe, Á., et al. (2014). A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges. Transportation Research Part E: Logistics and Transportation Review, 71, 111-128. doi:https://doi.org/10.1016/j.tre.2014.09.003
Froger, A., et al. (2017). A matheuristic for the electric vehicle routing problem with capacitated charging stations. Centre interuniversitaire de recherche sur les reseaux d'entreprise, la ….
Goeke, D., & Schneider, M. (2015). Routing a mixed fleet of electric and conventional vehicles. European Journal of Operational Research, 245(1), 81-99.
Greenhouse gas emission statistics - emission inventories. (2018). Retrieved from https://ec.europa.eu/eurostat/statistics-explained/index.php/Greenhouse_gas_emission_statistics#Trends_in_greenhouse_gas_emissions
Hemmelmayr, V. C., et al. (2012). An adaptive large neighborhood search heuristic for Two-Echelon Vehicle Routing Problems arising in city logistics. Computers & Operations Research, 39(12), 3215-3228. doi:https://doi.org/10.1016/j.cor.2012.04.007
Hiermann, G., et al. (2019). Routing a mix of conventional, plug-in hybrid, and electric vehicles. European Journal of Operational Research, 272(1), 235-248. doi:https://doi.org/10.1016/j.ejor.2018.06.025
Hiermann, G., et al. (2016). The electric fleet size and mix vehicle routing problem with time windows and recharging stations. European Journal of Operational Research, 252(3), 995-1018.
Hof, J., et al. (2017). Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops. Transportation Research Part B: Methodological, 97, 102-112.
International Energy Agency. (2012). CO2 Emissions from Fuel Combustion. Retrieved from Paris, France:
Jie, W., et al. (2019). The two-echelon capacitated electric vehicle routing problem with battery swapping stations: Formulation and efficient methodology. European Journal of Operational Research, 272(3), 879-904. doi:https://doi.org/10.1016/j.ejor.2018.07.002
Keskin, M., & Çatay, B. (2016). Partial recharge strategies for the electric vehicle routing problem with time windows. Transportation Research Part C: Emerging Technologies, 65, 111-127.
Keskin, M., & Çatay, B. (2018). A matheuristic method for the electric vehicle routing problem with time windows and fast chargers. Computers & Operations Research, 100, 172-188.
Li, J., et al. (2018). Heterogeneous fixed fleet vehicle routing problem based on fuel and carbon emissions. Journal of Cleaner Production, 201, 896-908. doi:https://doi.org/10.1016/j.jclepro.2018.08.075
Macrina, G., et al. (2019). An energy-efficient green-vehicle routing problem with mixed vehicle fleet, partial battery recharging and time windows. European Journal of Operational Research, 276(3), 971-982. doi:https://doi.org/10.1016/j.ejor.2019.01.067
Macrina, G., et al. (2019). The green mixed fleet vehicle routing problem with partial battery recharging and time windows. Computers & Operations Research, 101, 183-199.
Mancini, S. (2017). The Hybrid Vehicle Routing Problem. Transportation Research Part C: Emerging Technologies, 78, 1-12. doi:https://doi.org/10.1016/j.trc.2017.02.004
Martínez-Lao, J., et al. (2017). Electric vehicles in Spain: An overview of charging systems. Renewable and Sustainable Energy Reviews, 77, 970-983.
Montoya, A., et al. (2017). The electric vehicle routing problem with nonlinear charging function. Transportation Research Part B: Methodological, 103, 87-110.
Pelletier, S., et al. (2017). Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models. Transportation Research Part B: Methodological, 103, 158-187.
Ropke, S., & Pisinger, D. (2006). An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Science, 40(4), 455-472.
Sassi, O., et al. (2014). Vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles and time dependent charging costs.
Schiffer, M., et al. (2016). Are ECVs breaking even?–Competitiveness of electric commercial vehicles in medium–duty logistics networks. Working Paper OM-02/2016.
Schiffer, M., & Walther, G. (2017a). An adaptive large neighborhood search for the location-routing problem with intra-route facilities. Transportation Science, 52(2), 331-352.
Schiffer, M., & Walther, G. (2017b). The electric location routing problem with time windows and partial recharging. European Journal of Operational Research, 260(3), 995-1013.
Schneider, M., et al. (2014). The electric vehicle-routing problem with time windows and recharging stations. Transportation Science, 48(4), 500-520.
Shaw, P. (1997). A new local search algorithm providing high quality solutions to vehicle routing problems. APES Group, Dept of Computer Science, University of Strathclyde, Glasgow, Scotland, UK.
Touati-Moungla, N., & Jost, V. (2012). Combinatorial optimization for electric vehicles management. Journal of Energy and Power Engineering, 6(5), 738-743.
US Environmental Protection Agency. (2017). Routes to Lower Greenhouse Gas Emissions Transportation Future. Retrieved from https://www.epa.gov/greenvehicles/routes-lower-greenhouse-gas-emissions-transportation-future
US Environmental Protection Agency. (2018). Fast Facts on Transportation Greenhouse Gas Emissions. Retrieved from https://www.epa.gov/greenvehicles/fast-facts-transportation-greenhouse-gas-emissions
Yang, J., & Sun, H. (2015). Battery swap station location-routing problem with capacitated electric vehicles. Computers & Operations Research, 55, 217-232.
Zündorf, T. (2014). Electric vehicle routing with realistic recharging models.