Abstract
This paper introduces a new variant of the green vehicle routing problem with crowd-shipping. The company has an own mixed fleet composed of conventional combustion engine and electric vehicles. In addition, ordinary people named “occasional drivers” are available to deliver items to some customers on their route. The objective is to minimize the sum of routing costs of conventional and electric vehicles, by including fuel consumption cost and energy consumption cost, and occasional drivers’ compensation. We describe an integer linear programming formulation for the problem and we also provide a comprehensive analysis on several indicators, such as routing costs and polluting emissions. The results show how the use of occasional drivers may lead not only to more convenient solutions, but also to highly interesting scenarios in a green perspective.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Archetti, C., Savelsbergh, M., Speranza, M.G.: The vehicle routing problem with occasional drivers. Eur. J. Oper. Res. 254, 472–480 (2016)
Arslan, A.M., Agatz, N., Kroon, L., Zuidwijk, R.: Crowdsourced delivery: a dynamic pickup and delivery problem with ad-hoc drivers. In: Erasmus Research Institute of Management ERIM Paper, Social Science Research Network (2016). http://papers.ssrn.com/sol3/papers.cfm?abstracs_id=2726731
Bektaş, T., Laporte, G.: The pollution-routing problem. Transp. Res. Part B 45, 1232–1250 (2011)
Dahle, L., Andersson, H., Christiansen, M.: The vehicle routing problem with dynamic occasional drivers. In: Lecture Notes in Computer Science. 10572 LNCS, pp. 49-63 (2017)
Demir, E., Bektaş, T., Laporte, G.: An adaptive large neighborhood search heuristic for the pollution-routing problem. Eur. J. Oper. Res. 223, 346–359 (2012)
Erdoğan, S., Miller-Hooks, E.: A green vehicle routing problem. Transp. Res. Part E 48(1), 100–114 (2012)
Felipe, A., Ortuño, M.T., Righini, G., Tirado, G.: A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges. Transp. Res. Part E. 71, 111–128 (2014)
Franceschetti, A., Honhon, D., Van Woensel, T., Bektaş, T., Laporte, G.: The time-dependent pollution-routing problem. Transp. Res. Part B. 56, 265–293 (2013)
Koç, Ç., Bektaş, T., Jabali, O., Laporte, G.: The fleet size and mix pollution-routing problem. Transp. Res. Part B 70, 239–254 (2014)
Macrina, G., Di Puglia Pugliese, L., Guerriero, F., Laganà, D.: The vehicle routing problem with occasional drivers and time windows. In: Sforza, A., Sterle, C. (eds.) Optimization and Decision Science: Methodologies and Applications. Springer Proceedings in Mathematics & Statistics, vol. 217, pp. 577–587. ODS, Sorrento, Italy, Springer (2017)
Montoya, A., Guéret, C., Mendoza, J.E., Villegas, J.G.: The electric vehicle routing problem with nonlinear charging function. Transp. Res. Part B. 103, 87–110 (2017)
Schneider, M., Stenger, A., Goeke, D.: The electric vehicle routing problem with time windows and recharging stations. Transp. Sci. 48(4), 500–520 (2012)
Ubeda, S., Faulin, J., Serrano, A., Arcelus, F.J.: Solving the green capacitated vehicle routing problem using a tabu search algorithm. Lect. Notes Manag. Sci., J. Manuf. Syst. 6, 141–149 (2014)
Acknowledgements
This work was supported by MIUR “PRIN 2015” funds, project: Transportation and Logistics in the Era of Big Open Data - 2015JJLC3E_003 - CUP H52F15000190001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Macrina, G., Guerriero, F. (2018). The Green Vehicle Routing Problem with Occasional Drivers. In: Daniele, P., Scrimali, L. (eds) New Trends in Emerging Complex Real Life Problems. AIRO Springer Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-00473-6_38
Download citation
DOI: https://doi.org/10.1007/978-3-030-00473-6_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00472-9
Online ISBN: 978-3-030-00473-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)