首页> 外文会议>4th International Conference on Intelligent Data Engineering and Automated Learning IDEAL 2003 Mar 21-23, 2003 Hong Kong, China >A Hybrid Search Algorithm of Ant Colony Optimization and Genetic Algorithm Applied to Weapon-Target Assignment Problems
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A Hybrid Search Algorithm of Ant Colony Optimization and Genetic Algorithm Applied to Weapon-Target Assignment Problems

机译:蚁群算法和遗传算法的混合搜索算法在武器目标分配中的应用

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摘要

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.
机译:武器目标分配(WTA)问题是为目标找到合适的武器分配,目的是最大程度地减少对自身部队资产的预期损失。提出了一种新的蚁群优化(ACO)和遗传算法的混合算法来解决WTA问题。提出的算法是通过嵌入的ACO来提高遗传算法的搜索性能,从而具有局部最优的后代。该算法已成功应用于WTA问题。通过我们对这些测试问题的仿真,与其他现有搜索算法相比,该算法具有最佳性能。

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