A Brief Guide on the Modeling of Green Vehicle Routing Problems

Matheus Diógenes Andrade (), Rafael Kendy Arakaki () and Fábio Luiz Usberti ()
Additional contact information
Matheus Diógenes Andrade: University of Campinas
Rafael Kendy Arakaki: University of Campinas
Fábio Luiz Usberti: University of Campinas

A chapter in Handbook of Smart Energy Systems, 2023, pp 1081-1100 from Springer

Abstract: Abstract This chapter (Supported by FAPESP (proc. 2015/11937-9, 2018/25950-5) and by CNPq (proc. 435520/2018-0, 140328/2021-1)) provides mathematical tools and insights for an effective modeling of Green Vehicle Routing Problems (G-VRPs). The G-VRP, inspired by the green logistics, is an NP-hard problem that generalizes the Vehicle Routing Problem (VRP) allowing electric vehicles with limited range to recharge at Alternative Fuel Stations (AFSs) and keep servicing customers. Several insights, properties, inequalities, and preprocessing rules are presented for the modeling of G-VRPs using integer linear programming. The proposed contributions may improve exact methodologies by strengthening their mathematical formulations. The provided contents require some basic background on linear and integer programming.

Keywords: Vehicle routing problem; Valid inequalities; Optimization; Green logistics; Integer linear programming (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-97940-9_131

Ordering information: This item can be ordered from
http://www.springer.com/9783030979409

DOI: 10.1007/978-3-030-97940-9_131

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().