Simulated annealing whale radar resource scheduling algorithm based on Cauchy mutation

柯西变异的模拟退火鲸鱼雷达资源调度算法

¹ School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
² School of Mathematics and Statistics, Shaanxi Xueqian Normal University, Xi’an 710100, China
³ College of Air Defense and Anti-Missile, Air Force Engineering University, Xi’an 710043, China

Received: 13 October 2021

Abstract

In order to improve the effectiveness of radar resource scheduling, a Cauchy mutation simulated annealing whale radar resource scheduling algorithm is proposed in this study. The algorithm integrates the time resources, computing resources and the number of tasks completed of the radar. The algorithm is based on the degree of attribute matching between phased array radar data channels and tasks, so as to establish the task assignment model of the phased array radar for multiple targets. The idea of Cauchy mutation and simulated annealing is integrated into the whale optimization algorithm, which improves the optimization effect of the algorithm. Compared with the more popular camel optimization algorithm and balance optimization algorithm, the algorithm proposed in this paper has better performance in tracking task scheduling rate, average time shifting rate and scheduling value. The algorithm also shows excellent ability to solve the radar task scheduling issues.

摘要

为了提高雷达资源调度的有效性, 提出了柯西变异的模拟退火鲸鱼雷达资源调度算法。该算法综合雷达的时间资源、计算资源以及任务完成数量, 从相控阵雷达数据通道与任务间的属性匹配程度出发, 建立对多目标的相控阵雷达任务分配模型; 将柯西变异和模拟退火思想融入到鲸鱼优化算法中, 提高了算法的寻优效果。与比较流行的骆驼优化算法和平衡优化算法相比, 所提算法在跟踪任务调度率、平均时间偏移率和调度价值等方面都有较好的表现, 显示了该算法在解决雷达任务调度问题上的卓越能力。