Solving Weapon-Target Assignment Problems by a New Ant Colony Algorithm

• Published in: 2008 International Symposium on Computational Intelligence and Design Vol. 1; pp. 221 - 224
• Main Author: Gao Shang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2008
• Subjects: Algorithm design and analysis; Ant colony optimization; Biological cells; Computational intelligence; genetic algorithm; Genetic algorithms; Laboratories; Large-scale systems; Neural networks; Simulated annealing; Weapon-Target Assignment; Weapons
• ISBN: 0769533116; 9780769533117
• DOI: 10.1109/ISCID.2008.28

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.