Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98306
PIRA download icon_1.1View/Download Full Text
Title: Unmanned aerial vehicle scheduling problem for traffic monitoring
Authors: Li, M
Zhen, L
Wang, S 
Lv, W
Qu, X
Issue Date: Aug-2018
Source: Computers and industrial engineering, Aug. 2018, v. 122, p. 15-23
Abstract: For more accurate multiple-period real-time monitoring of road traffic, this paper investigates the unmanned aerial vehicle scheduling problem with uncertain demands. A mixed integer programming model is designed for this problem by combining the capacitated arc routing problem with the inventory routing problem. A local branching based solution method is developed to solve the model. A case study which applies this model to the road traffic in Shanghai is performed. In addition, numerical experiments are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution method.
Keywords: Arc routing problem
Inventory routing problem
Traffic monitoring
UAV routing problem
Publisher: Pergamon Press
Journal: Computers and industrial engineering 
ISSN: 0360-8352
EISSN: 1879-0550
DOI: 10.1016/j.cie.2018.05.039
Rights: © 2018 Elsevier Ltd. All rights reserved.
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Li, M., Zhen, L., Wang, S., Lv, W., & Qu, X. (2018). Unmanned aerial vehicle scheduling problem for traffic monitoring. Computers & Industrial Engineering, 122, 15-23 is available at https://doi.org/10.1016/j.cie.2018.05.039.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Wang_Unmanned_Aerial_Vehicle.pdfPre-Published version1.72 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

81
Citations as of Apr 14, 2025

Downloads

113
Citations as of Apr 14, 2025

SCOPUSTM   
Citations

65
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

46
Citations as of Oct 10, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.