摘要
蚁群优化算法是一种新型的模拟进化算法,也是一种随机型智能搜索算法。它具有信息素正反馈、稳健性强、易于与其他方法相结合等优点。将信息熵加入信息素启发因子中,得到动态调节的信息素启发因子,以此使蚁群算法具有自适应性,提出一种融入信息熵的自适应蚁群算法,并将此算法应用于战场雷达的频率指配中。通过仿真,不仅验证该算法的正确性和对战场雷达频率指配的适用性,也验证该算法优于一般蚁群算法。
Ant colony optimization algorithm is a new type of simulation evolution algorithm,and it is also a random intelligent search algorithm.It has the advantages of positive pheromone feedback,strong robustness,and is easy to combine with other methods.Information entropy is added to the pheromone heuristic factor to obtain a dynamically adjusted pheromone heuristic factor.Then an adaptive ant colony algorithm based on information entropy is proposed,and this algorithm is applied to the frequency assignment of battlefield radar.The correctness of the algorithm and its applicability of the battlefield radar's frequency assignment are verified with the simulation,but also it is verified that the proposed algorithm is superior to the general ant colony algorithm.
作者
李娅
万海旭
钟立俊
LI Ya;WAN Haixu;ZHONG Lijun(Science and Technology on Electronic Information Control Laboratory,Chengdu 610036,China)
出处
《电子信息对抗技术》
北大核心
2021年第1期79-84,共6页
Electronic Information Warfare Technology
关键词
频率指配
蚁群算法
信息素
frequency assignment
ant colony algorithm
pheromone
