A hybrid optimization framework for UAV reconnaissance mission planning. (November 2022)
- Record Type:
- Journal Article
- Title:
- A hybrid optimization framework for UAV reconnaissance mission planning. (November 2022)
- Main Title:
- A hybrid optimization framework for UAV reconnaissance mission planning
- Authors:
- Liu, Wei
Zhang, Tao
Huang, Shengjun
Li, Kaiwen - Abstract:
- Abstract: Applying unmanned aerial vehicles (UAVs) in military reconnaissance missions arises in recent years. It refers to using finite UAVs to reconnoiter some enemy targets with limited battery power, aiming at collecting valuable information as much as possible. While existing methods like heuristics and intelligent optimization methods have been widely applied, their performance on large-scale reconnaissance mission planning problems (RMPPs) is still unsatisfactory. This study proposes a hybrid optimization framework, namely, EA-DRL, to improve the optimization effect based on a problem decomposition strategy. In detail, the RMPP is decomposed into a target selection subproblem and a path planning subproblem. An evolutionary algorithm and a deep reinforcement learning method are proposed to solve them, respectively. Updating solutions to these two subproblems iteratively eventually completes the optimization of the given RMPP. Experimental results on different types of RMPP instances show great effectiveness and strong generalization ability of the proposed framework EA-DRL. Highlights: A decomposition strategy for UAV reconnaissance mission planning problems (RMPPs). A hybridization of evolutionary algorithms and deep reinforcement learning methods. A useful method which can be extended for solving multi-objective RMPPs. An efficient population initialization method.
- Is Part Of:
- Computers & industrial engineering. Volume 173(2022)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 173(2022)
- Issue Display:
- Volume 173, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 173
- Issue:
- 2022
- Issue Sort Value:
- 2022-0173-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-11
- Subjects:
- Reconnaissance mission planning -- Decomposition -- Optimization -- Evolutionary algorithms -- Deep reinforcement learning
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2022.108653 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24154.xml