A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem
Joint Authors
Li, You
Kou, Yingxin
Li, Zhanwu
Xu, An
Chang, Yizhe
Source
International Journal of Aerospace Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-16
Country of Publication
Egypt
No. of Pages
14
Abstract EN
The weapon-target assignment (WTA) problem, known as an NP-complete problem, aims at seeking a proper assignment of weapons to targets.
The biobjective WTA (BOWTA) optimization model which maximizes the expected damage of the enemy and minimizes the cost of missiles is designed in this paper.
A modified Pareto ant colony optimization (MPACO) algorithm is used to solve the BOWTA problem.
In order to avoid defects in traditional optimization algorithms and obtain a set of Pareto solutions efficiently, MPACO algorithm based on new designed operators is proposed, including a dynamic heuristic information calculation approach, an improved movement probability rule, a dynamic evaporation rate strategy, a global updating rule of pheromone, and a boundary symmetric mutation strategy.
In order to simulate real air combat, the pilot operation factor is introduced into the BOWTA model.
Finally, we apply the MPACO algorithm and other algorithms to the model and compare the data.
Simulation results show that the proposed algorithm is successfully applied in the field of WTA which improves the performance of the traditional P-ACO algorithm effectively and produces better solutions than the two well-known multiobjective optimization algorithms NSGA-II and SPEA-II.
American Psychological Association (APA)
Li, You& Kou, Yingxin& Li, Zhanwu& Xu, An& Chang, Yizhe. 2017. A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem. International Journal of Aerospace Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1157846
Modern Language Association (MLA)
Li, You…[et al.]. A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem. International Journal of Aerospace Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1157846
American Medical Association (AMA)
Li, You& Kou, Yingxin& Li, Zhanwu& Xu, An& Chang, Yizhe. A Modified Pareto Ant Colony Optimization Approach to Solve Biobjective Weapon-Target Assignment Problem. International Journal of Aerospace Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1157846
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1157846