TY - JOUR
T1 - Routing Problem for Unmanned Aerial Vehicle Patrolling Missions - A Progressive Hedging Algorithm
AU - Rajan, Sudarshan
AU - Sundar, Kaarthik
AU - Gautam, Natarajan
N1 - Funding Information:
Kaarthik Sundar would like to acknowledge the funding provided by LANL’s Directed Research and Development (LDRD), USA project: “ 20200603ECR : Distributed Algorithms for Large-Scale Ordinary Differential/Partial Differential Equation (ODE/PDE) Constrained Optimization Problems on Graphs”. This work was carried out under the U.S. DOE Contract No. DE-AC52-06NA25396.
Funding Information:
Kaarthik Sundar would like to acknowledge the funding provided by LANL's Directed Research and Development (LDRD), USA project: ?20200603ECR: Distributed Algorithms for Large-Scale Ordinary Differential/Partial Differential Equation (ODE/PDE) Constrained Optimization Problems on Graphs?. This work was carried out under the U.S. DOE Contract No. DE-AC52-06NA25396.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/6
Y1 - 2022/6
N2 - The paper presents a two-stage stochastic program to model a routing problem involving an Unmanned Aerial Vehicle (UAV) in the context of patrolling missions. In particular, given a set of targets and a set of supplemental targets corresponding to each target, the first stage decisions involve finding the sequence in which the vehicle has to visit the set of targets. Upon reaching each target, the UAV collects information and if the operator of the UAV deems that the information collected is not of sufficient fidelity, then the UAV has to visit all the supplemental targets corresponding to that target to collect additional information before proceeding to visit the next target. The problem is solved using a progressive hedging algorithm and extensive computational results corroborating the effectiveness of the proposed model and the solution methodology is presented.
AB - The paper presents a two-stage stochastic program to model a routing problem involving an Unmanned Aerial Vehicle (UAV) in the context of patrolling missions. In particular, given a set of targets and a set of supplemental targets corresponding to each target, the first stage decisions involve finding the sequence in which the vehicle has to visit the set of targets. Upon reaching each target, the UAV collects information and if the operator of the UAV deems that the information collected is not of sufficient fidelity, then the UAV has to visit all the supplemental targets corresponding to that target to collect additional information before proceeding to visit the next target. The problem is solved using a progressive hedging algorithm and extensive computational results corroborating the effectiveness of the proposed model and the solution methodology is presented.
KW - Integer programming
KW - Progressive-hedging
KW - Routing
KW - Two-stage stochastic program
KW - Unmanned Aerial Vehicles
UR - http://www.scopus.com/inward/record.url?scp=85124488513&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85124488513&partnerID=8YFLogxK
U2 - 10.1016/j.cor.2022.105702
DO - 10.1016/j.cor.2022.105702
M3 - Article
AN - SCOPUS:85124488513
SN - 0305-0548
VL - 142
JO - Computers and Operations Research
JF - Computers and Operations Research
M1 - 105702
ER -