Abstract
Weapon-Target Assignment (WTA) problems are to find a proper assignment of weapons to targets with the objective of minimizing the expected damage of own-force asset. In this paper, a novel hybrid algorithm of ant colony optimization (ACO) and genetic algorithm is proposed to solve WTA problems. The proposed algorithm is to enhance the search performance of genetic algorithms by embedded ACO so as to have locally optimal offspring. This algorithm is successfully applied to WTA problems. From our simulations for those tested problems, the proposed algorithm has the best performance when compared to other existing search algorithms.
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Lee, ZJ., Lee, WL. (2003). A Hybrid Search Algorithm of Ant Colony Optimization and Genetic Algorithm Applied to Weapon-Target Assignment Problems. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_37
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DOI: https://doi.org/10.1007/978-3-540-45080-1_37
Publisher Name: Springer, Berlin, Heidelberg
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