EconPapers    
Economics at your fingertips  
 

Robust vehicle routing with drones under uncertain demands and truck travel times in humanitarian logistics

Yunqiang Yin, Yongjian Yang, Yugang Yu, Dujuan Wang and T.C.E. Cheng

Transportation Research Part B: Methodological, 2023, vol. 174, issue C

Abstract: Resource transport in the aftermath of disasters is critical, yet in the absence of sufficient historical data or accurate forecasting approaches, the development of resource transport strategies often faces the challenge of dealing with uncertainty, especially uncertainties in demand and travel time. In this paper we investigate the vehicle routing problem with drones under uncertain demands and truck travel times. Specifically, there is a set of trucks and drones (each truck is associated with a drone) collaborating to transport relief resources to the affected areas, where a drone can be launched from its associated truck at a node, independently transporting relief resources to one or more of the affected areas, and returning to the truck at another node along the truck route. For this problem, we present a tailored robust optimization model based on the well-known budgeted uncertainty set, and develop an enhanced branch-and-price-and-cut algorithm incorporating a bounded bidirectional labelling algorithm to solve the pricing problem, which can be modelled as a robust resource-constrained vehicle and drone synthetic shortest path problem. To enhance the performance of the algorithm, we employ subset-row inequalities to tighten the lower bound and incorporate some enhancement strategies to quickly solve the pricing problem. We perform extensive numerical studies to assess the performance of the developed algorithm, discuss the benefits of considering uncertainty and robustness, and analyse the impacts of key model parameters on the optimal solution. We also evaluate the benefits of the truck–drone collaborative transport mode over the truck-only transport mode through a real case study of the 2008 earthquake in Wenchuan, China.

Keywords: Transport; Humanitarian logistics; Robust optimization; Truck–drone collaborative transport mode; Branch-and-price-and-cut algorithm (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0191261523001042
Full text for ScienceDirect subscribers only

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:eee:transb:v:174:y:2023:i:c:s0191261523001042

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.trb.2023.102781

Access Statistics for this article

Transportation Research Part B: Methodological is currently edited by Fred Mannering

More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:transb:v:174:y:2023:i:c:s0191261523001042