skip to main content

DOE PAGESDOE PAGES

Title: A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption

The past decade has seen a substantial increase in the use of small unmanned aerial vehicles (UAVs) in both civil and military applications. This article addresses an important aspect of refueling in the context of routing multiple small UAVs to complete a surveillance or data collection mission. Specifically, this article formulates a multiple-UAV routing problem with the refueling constraint of minimizing the overall fuel consumption for all the vehicles as a two-stage stochastic optimization problem with uncertainty associated with the fuel consumption of each vehicle. The two-stage model allows for the application of sample average approximation (SAA). Although the SAA solution asymptotically converges to the optimal solution for the two-stage model, the SAA run time can be prohibitive for medium- and large-scale test instances. Hence, we develop a tabu search-based heuristic that exploits the model structure while considering the uncertainty in fuel consumption. Extensive computational experiments corroborate the benefits of the two-stage model compared to a deterministic model and the effectiveness of the heuristic for obtaining high-quality solutions.
Authors:
 [1] ;  [2] ;  [3]
  1. Wayne State Univ., Detroit, MI (United States). Dept. of Industrial and Systems Engineering
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Texas A & M Univ., College Station, TX (United States). Dept. of Mechanical Engineering
Publication Date:
Report Number(s):
LA-UR-18-29794
Journal ID: ISSN 1424-8220
Grant/Contract Number:
89233218CNA000001
Type:
Accepted Manuscript
Journal Name:
Sensors
Additional Journal Information:
Journal Volume: 18; Journal Issue: 11; Journal ID: ISSN 1424-8220
Publisher:
MDPI AG
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE; LANL Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; vehicle routing; unmanned aerial vehicles; fuel constraints; two-stage stochastic optimization; sample average approximation; tabu search
OSTI Identifier:
1483552

Venkatachalam, Saravanan, Sundar, Kaarthik, and Rathinam, Sivakumar. A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption. United States: N. p., Web. doi:10.3390/s18113756.
Venkatachalam, Saravanan, Sundar, Kaarthik, & Rathinam, Sivakumar. A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption. United States. doi:10.3390/s18113756.
Venkatachalam, Saravanan, Sundar, Kaarthik, and Rathinam, Sivakumar. 2018. "A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption". United States. doi:10.3390/s18113756. https://www.osti.gov/servlets/purl/1483552.
@article{osti_1483552,
title = {A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption},
author = {Venkatachalam, Saravanan and Sundar, Kaarthik and Rathinam, Sivakumar},
abstractNote = {The past decade has seen a substantial increase in the use of small unmanned aerial vehicles (UAVs) in both civil and military applications. This article addresses an important aspect of refueling in the context of routing multiple small UAVs to complete a surveillance or data collection mission. Specifically, this article formulates a multiple-UAV routing problem with the refueling constraint of minimizing the overall fuel consumption for all the vehicles as a two-stage stochastic optimization problem with uncertainty associated with the fuel consumption of each vehicle. The two-stage model allows for the application of sample average approximation (SAA). Although the SAA solution asymptotically converges to the optimal solution for the two-stage model, the SAA run time can be prohibitive for medium- and large-scale test instances. Hence, we develop a tabu search-based heuristic that exploits the model structure while considering the uncertainty in fuel consumption. Extensive computational experiments corroborate the benefits of the two-stage model compared to a deterministic model and the effectiveness of the heuristic for obtaining high-quality solutions.},
doi = {10.3390/s18113756},
journal = {Sensors},
number = 11,
volume = 18,
place = {United States},
year = {2018},
month = {11}
}