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
Link To Document :
بازگشت