Advertisement

Green Vehicle Routing Problem: A Critical Survey

  • Kedar Nath Das
  • Rajeev DasEmail author
Conference paper
  • 77 Downloads
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 12)

Abstract

Over the time, the number of vehicles is increasing exponentially, that results in increasing \( CO_{2} \) emission in the environment. On the other hand, people attempt to recommend a collection of optimal paths for a vehicle fleet to travel and deliver goods to the customers in a minimum time period. Combining both above fleets gives rise to a Green Vehicle Routing Problem (GVRP). Since about the last two decades, researchers suggest many GVRP algorithms to serve the society. In this study, a critical review on different and recent trends in GVRP is made. Based on the thorough study, some of the future scopes on the related area are suggested as a concluding remark.

Keywords

Green vehicle routing Optimization Meta-heuristics Load carrying vehicles Fuel consumption \( CO_{2} \) emission Alternative fuel-powered vehicles 

Notes

Acknowledgements

Authors would like to thank TEQIP-III, INDIA to support the travel grant to present the paper in ICIMSAT-2019.

References

  1. 1.
    Tang, J., Zhang, J., Pan, Z.: A scatter search algorithm for solving vehicle routing problem with loading cost. Expert Syst. Appl. 37, 4073–4083 (2010)CrossRefGoogle Scholar
  2. 2.
    Erdoğan, S., Miller-Hooks, E.: A green vehicle routing problem. Transp. Res. Part E 109(1), 100–114 (2012)CrossRefGoogle Scholar
  3. 3.
    Jemai, J., Zekri, M., Mellouli, K.: An NSGA-II algorithm for the green vehicle routing problem. In: 12th European Conference (EvoCOP), pp. 37–48 (2012)Google Scholar
  4. 4.
    Salimifard, K., Raeesi, R.: A green routing problem: optimising CO2 emissions and costs from a bi-fuel vehicle fleet. Int. J. Adv. Oper. Manag. 6(1), 27–57 (2014)Google Scholar
  5. 5.
    Taha, M., Fors, N., Shoukry, A.A.: An exact solution for a class of green vehicle routing problem. In: International Conference on Industrial Engineering and Operations Management, Bali, Indonesia, pp. 1383–1390 (2014)Google Scholar
  6. 6.
    Lin, C., Choy, K.L., Ho, G.T.S., Chung, S.H., Lam, H.Y.: Survey of green vehicle routing problem: past and future trends, 41, 1118–1138 (2014)Google Scholar
  7. 7.
    Tiwari, A., Chang, P.-C.: A block recombination approach to solve green vehicle routing problem. Int. J. Prod. Econ. 164, 379–387 (2015)CrossRefGoogle Scholar
  8. 8.
    Koҁ, Ҁ., Karaoglan, I.: The green vehicle routing problem: a heuristic based exact solution approach. Appl. Soft Comput. 39, 154–164 (2016)CrossRefGoogle Scholar
  9. 9.
    Ene, S., Küҁükoğlu, I., Aksoy, A., Ӧztürk, N.: A hybrid meta-heuristic algorithm for the green vehicle routing problem with a heterogeneous fleet. Int. J. Veh. Des. 71(1–4), 75–102 (2016)CrossRefGoogle Scholar
  10. 10.
    Moutaoukil, A., Neubert, G., Derrouiche, R.: A comparison of homogeneous and heterogeneous vehicle fleet size in green vehicle routing problem. In: IFIP International Conference on Advances in Production Management Systems (APMS), IFIP Advances in Information and Communication Technology, AICT-439 (Part II), September 2014, pp. 450–457. Springer, Ajaccio (2014)Google Scholar
  11. 11.
    Xiao, Y., Konak, A.: The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion. Transp. Res. Part E 88, 146–166 (2016)CrossRefGoogle Scholar
  12. 12.
    Tunga, H., Bhaumik, A.K.: A method for solving bi-objective green vehicle routing problem through genetic algorithm. J. Assoc. Eng. India 87(1–2), 33–48 (2016)Google Scholar
  13. 13.
    Sawik, B., Faulin, J., Pérez-Bernabeu, E.: Multi-criteria analysis for the green VRP: a case discussion for the distribution problem of a spanish retailer. Transp. Res. Procedia 22, 305–313 (2017)CrossRefGoogle Scholar
  14. 14.
    Mirmohammadi, S.H., Babaee Tirkolaee, E., Goli, A., Dehnaviarani, S.: The periodic green vehicle routing problem with considering of time-dependent urban traffic and time windows, 7(1), 143–156 (2017)Google Scholar
  15. 15.
    Messaoud, E., El Idrissi, A.E., Alaoui, A.E.: The green dynamic vehicle routing problem in sustainable transport. In: 4th International Conference on Logistics Operations Management, pp. 1–6 (2018)Google Scholar
  16. 16.
    da Costa, P.R., Mauceri, S., Carroll, P., Pallonetto, F.: A genetic algorithm for a green vehicle routing problem. Electron. Notes Discret. Math. 64, 65–74 (2018)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Zhang, S., Gajpal, Y., Appadoo, S.S.: A meta-heuristic for capacitated green vehicle routing problem. Ann. Oper. Res. 269, 753–771 (2018)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Poonthalir, G., Nadarajan, R.: A fuel efficient green vehicle routing problem with varying speed constraints (F-GVRP). Expert Syst. Appl. 100, 131–144 (2018)CrossRefGoogle Scholar
  19. 19.
    Rabbani, M., Bosjin, S.A., Yazdanparast, R., Saravi, N.A.: A stochastic time-dependent green capacitated vehicle routing and scheduling problem with time window, resiliency and reliability: a case study. Decis. Sci. Lett. 7, 381–394 (2018)CrossRefGoogle Scholar
  20. 20.
    Kazemian, I., Rabbani, M., Farrokhi-Asl, H.: A way to optimally solve a green time-dependent vehicle routing problem with time windows. Comput. Appl. Math. 37, 2766–2783 (2018)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Tirkolaee, E.B., Hosseinabadi, A.A., Soltani, M., Sangaiah, A.K., Wang, J.: A hybrid genetic algorithm for multi-trip green capacitated arc routing problem in the scope of urban services. Sustainability 10, 1–21 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of MathematicsNational Institute of Technology SilcharSilcharIndia

Personalised recommendations