DocumentCode
2020455
Title
Solving Weapon-Target Assignment Problems by a New Ant Colony Algorithm
Author
Shang, Gao
Author_Institution
Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., Zhenjiang
Volume
1
fYear
2008
fDate
17-18 Oct. 2008
Firstpage
221
Lastpage
224
Abstract
A new ant colony algorithm for weapon-target assignment (WTA) problems is proposed. The proposed algorithm is a parallel mechanism based on ant colony optimization (ACO) and has cooperative interactions among ant colonies. It has both the advantage of ACO, the ability to find feasible solutions and to avoid premature convergence, and the advantage of heuristics, the ability to conduct fine-tuning to find better solutions. A comparison of the proposed algorithm with several existing search approaches shows that the new algorithm outperforms its competitors on all tested WTA problems.
Keywords
military systems; optimisation; ant colony algorithm; ant colony optimization; weapon-target assignment problems; Algorithm design and analysis; Ant colony optimization; Biological cells; Computational intelligence; Genetic algorithms; Laboratories; Large-scale systems; Neural networks; Simulated annealing; Weapons; Weapon-Target Assignment; ant colony optimization; genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3311-7
Type
conf
DOI
10.1109/ISCID.2008.28
Filename
4725595
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