摘要
针对火力规划问题(WTA),提出了一种新的混合智能算法,该算法在传统蚁群算法的基础上融入遗传算法与粒子群算法,通过添加初始信息素与蚂蚁的经验信息,缩短了寻找最优解的时间,提高了计算效率。利用MATLAB对算法编程实现,通过程序展示算法理论,最后求解简单的火力规划模型,对比传统智能算法与混合智能算法的计算过程,结果证明了混合智能算法求解WTA问题的正确性与高效性,与传统蚁群算法、遗传算法相比,它能够较明显地缩短最优解出现的时间。
A hybrid intelligent algorithm is derived to solve the Weapon-Target Assignment(WTA)problem.The genetic algorithm and the Particle Swarm Optimization are integrated into the ant colony algorithm to form the hybrid.Initial pheromone and experience information are added into the new method to reduce the time to find the best solution and to improve the efficiency of calculation.The new algorithm is realized by MATLAB programming and the theory is presented during the process.At last,a simple WTA model is solved by traditional intelligent algorithms and the new hybrid.The iterative procedures and the computing results are compared between these algorithms.It proves the accuracy and highly efficiency of the hybrid and it reduces the calculation time to a certain degree.
作者
郭莹莹
张志刚
Guo Yingying;Zhang Zhigang(The Academy of Mathematics,University of Science and Technology Beijing,Beijing 100083,China)
出处
《战术导弹技术》
北大核心
2019年第5期103-109,共7页
Tactical Missile Technology
关键词
火力规划
智能算法
遗传算法
weapon-target assignment
intelligent-algorithm
genetic algorithm
