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

Venkatachalam, Saravanan; Sundar, Kaarthik; Rathinam, Sivakumar

doi:10.3390/s18113756

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

Journal Article · Sat Nov 03 00:00:00 EDT 2018 · Sensors

DOI:https://doi.org/10.3390/s18113756· OSTI ID:1483552

Venkatachalam, Saravanan ^[1]; Sundar, Kaarthik ^[2]; Rathinam, Sivakumar ^[3]

Wayne State Univ., Detroit, MI (United States). Dept. of Industrial and Systems Engineering
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Texas A & M Univ., College Station, TX (United States). Dept. of Mechanical Engineering

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.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE; LANL Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1483552

Report Number(s):: LA-UR-18-29794

Journal Information:: Sensors, Vol. 18, Issue 11; ISSN 1424-8220

Publisher:: MDPI AGCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 12 works

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