Improved Ant Colony Optimization for Weapon-Target Assignment
Joint Authors
Wang, Jun
Hu, Xinwu
Zhang, Xiaonan
Luo, Pengcheng
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-11
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Weapon-target assignment (WTA) which is crucial in cooperative air combat explores assigning weapons to targets with the objective of minimizing the threats from those targets.
Based on threat functions, there are four WTA models constrained by the payload and other tactical requirements established.
The improvements of ant colony optimization are integrated with respect to the rules of path selection, pheromone update, and pheromone concentration interval, and algorithm AScomp is proposed based on the elite strategy of ant colony optimization (ASrank).
We add garbage ants to ASrank; when the pheromone is updated, the elite ants are rewarded and the garbage ants are punished.
A WTA algorithm is designed based on the improved ant colony optimization (WIACO).
For the purpose of demonstration of WIACO in air combat, a real-time WTA simulation algorithm (RWSA) is proposed to provide the results of average damage, damage rate, and kill ratio.
The following conclusions are drawn: (1) the third WTA model, considering the threats of both sides and hit probabilities, is the most effective among the four; (2) compared to the traditional ant colony algorithm, the WIACO requires fewer iterations and avoids local optima more effectively; and (3) WTA is better conducted when any fighter is shot down or any fighter’s missiles run out than along with the flight.
American Psychological Association (APA)
Hu, Xinwu& Luo, Pengcheng& Zhang, Xiaonan& Wang, Jun. 2018. Improved Ant Colony Optimization for Weapon-Target Assignment. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1208419
Modern Language Association (MLA)
Hu, Xinwu…[et al.]. Improved Ant Colony Optimization for Weapon-Target Assignment. Mathematical Problems in Engineering No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1208419
American Medical Association (AMA)
Hu, Xinwu& Luo, Pengcheng& Zhang, Xiaonan& Wang, Jun. Improved Ant Colony Optimization for Weapon-Target Assignment. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1208419
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208419