EXACT OPTIMIZATION APPROACHES FOR SURVEILLANCE AND DEFENSE OPERATIONS WITH UNMANNED AERIAL VEHICLES UNDER UNCERTAINTY
Abstract
Recent technological advances have increased the application areas where the use of Unmanned Aerial Vehicles (UAVs) can significantly improve operations. UAVs are particularly useful in Air Force applications that require operating in adversarial territory such as supply, logistics, and surveillance. However, due to their physical fragility, as well as to their wireless connectivity requirements, UAVs are highly prone to adversarial cyber-physical attacks that can physically destroy them or render them otherwise inoperable. While the importance of UAVs has been recognized by the scientific literature, the methods to optimize the operation of UAVs, particularly under uncertain adversarial attacks, are limited, and most of the existing literature relies on heuristic approaches or restrictive assumptions to simplify the problems. The overall goal of this project is to provide a mathematical and algorithmic framework to model and optimally solve routing and re-routing problems for intelligence, surveillance, and reconnaissance operations with UAVs under uncertain adversarial disruptions. The proposed framework will be based on mixed-integer programming. It will provide parsimonious formulations that will be solved by integrating column and constraint generation decomposition algorithms with decision diagrams-based techniques. The methods will allow planners to find optimal routing plans for a fleet composed of UAVs and ground vehicles and will allow them to optimally re-route the fleet if it is necessary to react to uncertain adversarial disruptions. Contributions will be made both theoretically and computationally to the area of two-stage routing optimization under uncertainty, resulting in articles published in the leading optimization journals. Moreover, the proposed research has sparked the interest of personnel at the Air Force Research Laboratory. This collaboration could result in prototyping the developments in real-world scenarios encountered by the Air Force.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502210236
Entities
People
- Juan Borrero
Organizations
- Air Force Office of Scientific Research
- Oklahoma State University–Stillwater
- United States Air Force