Improved Firefly Algorithm And Its Application In Array Antenna

In recent years,with the progress of science and the rapid development of society,the problem of optimization is becoming more complex and larger.Therefore,it is of great significance to seek an efficient and universal intelligent optimization algorithm.As an important branch of the stochastic optimization algorithm,the swarm intelligence algorithm is widely used by many researchers because of its strong adaptability and can be used to solve the complex optimization problems that traditional deterministic optimization algorithms are difficult to solve.As a newly proposed swarm intelligence algorithm,firefly algorithm has some advantag es such as simple concept and easy to implement,and local optimization avoidance.But th ere are still some problems such as insufficient global searching ability and slow convergen ce rate in high-dimensional complex problems.In view of this,this paper has made improv ements to the firefly algorithm,and the improved firefly algorithm has been used in the fie ld of antenna design.The main research results of this paper are shown as follows:The standard firefly algorithm is studied from the basic principle and mathematical model,and the advantages and disadvantages of the firefly algorithm are summed up by comparing two common swarm intelligence algorithm of particle swarm optimization and artificial bee colony algorithm,and it provides an idea for the improvement of the algorithm.In order to improve the global optimization ability and accelerate the convergence speed of the firefly algorithm,this paper improves the firefly algorithm.Firstly,the firefly population is uniformly initialized by the principle of good point set to improve the quality of initial solution and make the population more diversified.Secondly,the variable parameter step size ? of the algorithm is studied theoretically,and a dynamic adjustment step mechanism is proposed to balance the global optimization and convergence speed of the algorithm.Then,by introducing the global best individual,the position updating formula of the original algorithm is changed,and the position of the best particle is updated based on the change of the dimension,which makes the algorithm easier to jump out of the local optimum and enhance the global optimization ability.At last,the test results of seven standard test functions show that the improved algorithm not only has high convergence speed but also has high precision.The improved firefly algorithm is applied to the pattern synthesis of the array antenna.The simulation results show that the improved algorithm has better optimization effect than the traditional optimization method and the standard firefly algorithm.