By Topic

Air Combat Decision-Making for Cooperative Multiple Target Attack Using Heuristic Adaptive Genetic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
De-Lin Luo ; College of Automation Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing, 210016, China; E-MAIL: luodelin602@163.com ; Chun-Lin Shen ; Biao Wang ; Wen-Hai Wu

The Decision-Making (DM) problem is investigated for Cooperative Multiple Target Attack in air combat. It is to search for a proper attack assignment of M friendly fighters, with multiple target attack capability, to N hostile fighters called targets to achieve an optimal missile-target attack effect. Thus, Missile-Target Assignment (MTA) is regarded as the main part of the DM problem and has to be solved firstly. Then, the DM solution is derived from the optimal MTA solution. To the MTA problem, a Heuristic Adaptive Genetic Algorithm (HAGA) is proposed to search for its optimal solution. The HAGA utilizes specific heuristic knowledge to improve the search capability of the Adaptive Genetic Algorithm (AGA). Simulation results show that the HAGA is effective and has much better performance than the AGA.

Published in:

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on  (Volume:1 )

Date of Conference:

18-21 Aug. 2005