Abstract
The capacitated green vehicle routing problem is considered in this paper as a new variant of the vehicle routing problem. In this problem, alternative fuel-powered vehicles (AFVs) are used for distributing products. AFVs are assumed to have low fuel tank capacity. Therefore, during their distribution process, AFVs are required to visit alternative fuel stations (AFSs) for refueling. The design of the vehicle routes for AFVs becomes difficult due to the limited loading capacity, the low fuel tank capacity and the scarce availability of AFSs. Two solution methods, the two-phase heuristic algorithm and the meta-heuristic based on ant colony system, are proposed to solve the problem. The numerical experiment is performed on the randomly generated problem instances to evaluate the performance of the proposed algorithms.





Similar content being viewed by others
References
Abdulkader, M. M., Gajpal, Y., & ElMekkawy, T. Y. (2015). Hybridized ant colony algorithm for the multi compartment vehicle routing problem. Applied Soft Computing, 37, 196–203.
Barán, B., & Schaerer, M. (2003). A multiobjective ant colony system for vehicle routing problem with time windows. In Paper presented at the applied informatics.
Bard, J. F., Huang, L., Dror, M., & Jaillet, P. (1998). A branch and cut algorithm for the VRP with satellite facilities. IIE Transactions, 30(9), 821–834.
Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232–1250.
Bell, J. E., & McMullen, P. R. (2004). Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics, 18(1), 41–48.
Colorni, A., Dorigo, M., & Maniezzo, V. (1991). Distributed optimization by ant colonies. In Paper presented at the proceedings of the first European conference on artificial life.
Crevier, B., Cordeau, J.-F., & Laporte, G. (2007). The multi-depot vehicle routing problem with inter-depot routes. European Journal of Operational Research, 176(2), 756–773.
Demir, E., Bektaş, T., & Laporte, G. (2012). An adaptive large neighborhood search heuristic for the pollution-routing problem. European Journal of Operational Research, 223(2), 346–359.
Dorigo, M., & Stützle, T. (2004). Ant colony optimization. Bradford, Cambirdge: Massachusetts Institute of Technology, MIT Press.
Erdoğan, S., & Miller-Hooks, E. (2012). A green vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 48(1), 100–114.
Felipe, Á., Ortuño, M. T., Righini, G., & Tirado, G. (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.
Fraer, R., Dinh, H., Chandler, K., & Buchholz, B. (2005). Operating experience and teardown analysis for engines operated on biodiesel blends (B20). SAE Technical Paper, 2, 005-001.
Franceschetti, A., Honhon, D., Van Woensel, T., Bektaş, T., & Laporte, G. (2013). The time-dependent pollution-routing problem. Transportation Research Part B: Methodological, 56, 265–293.
Gajpal, Y., & Abad, P. (2009a). An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup. Computers and Operations Research, 36(12), 3215–3223.
Gajpal, Y., & Abad, P. (2009b). Multi-ant colony system (MACS) for a vehicle routing problem with backhauls. European Journal of Operational Research, 196(1), 102–117.
Gutin, G., Yeo, A., & Zverovich, A. (2002). Traveling salesman should not be greedy: Domination analysis of greedy-type heuristics for the TSP. Discrete Applied Mathematics, 117(1), 81–86.
IEA (2014). CO\(_{2}\) emissions from fuel combustion highlights 2014. Paris: International Energy Agency, pp 10.
IEA (2015). CO\(_{2}\) emissions from fuel combustion highlights 2015. Paris: International Energy Agency, pp 7–11.
Kek, A. G., Cheu, R. L., & Meng, Q. (2008). Distance-constrained capacitated vehicle routing problems with flexible assignment of start and end depots. Mathematical and Computer Modelling, 47(1), 140–152.
Koç, Ç., Bektaş, T., Jabali, O., & Laporte, G. (2014). The fleet size and mix pollution-routing problem. Transportation Research Part B: Methodological, 70, 239–254.
Kuo, Y. (2010). Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Computers and Industrial Engineering, 59(1), 157–165.
Lin, C., Choy, K. L., Ho, G. T., Chung, S., & Lam, H. (2014). Survey of green vehicle routing problem: Past and future trends. Expert Systems with Applications, 41(4), 1118–1138.
Mehrez, A., & Stern, H. I. (1985). Optimal refueling strategies for a mixed—Vehicle fleet. Naval Research Logistics Quarterly, 32(2), 315–328.
Mehrez, A., Stern, H. I., & Ronen, D. (1983). Vehicle fleet refueling strategies to maximize operational range. Naval Research Logistics Quarterly, 30(2), 319–342.
Sbihi, A., & Eglese, R. W. (2007). Combinatorial optimization and green logistics. 4OR, 5(2), 99–116.
Schneider, M., Stenger, A., & Goeke, D. (2014). The electric vehicle-routing problem with time windows and recharging stations. Transportation Science, 48(4), 500–520.
Stützle, T., & Hoos, H. H. (2000). MAX–MIN ant system. Future Generation Computer Systems, 16(8), 889–914.
Tarantilis, C. D., Zachariadis, E. E., & Kiranoudis, C. T. (2008). A hybrid guided local search for the vehicle-routing problem with intermediate replenishment facilities. INFORMS Journal on Computing, 20(1), 154–168.
Xiao, Y., Zhao, Q., Kaku, I., & Xu, Y. (2012). Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Computers and Operations Research, 39(7), 1419–1431.
Acknowledgements
This research is partially supported by University Start-up Research Grant from Asper School of Business, University of Manitoba, Canada.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, S., Gajpal, Y. & Appadoo, S.S. A meta-heuristic for capacitated green vehicle routing problem. Ann Oper Res 269, 753–771 (2018). https://doi.org/10.1007/s10479-017-2567-3
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-017-2567-3