An Improved Firefly Algorithm And Its Application

Firefly algorithm is a new type of meta-heuristic algorithm,which has the characteristics of simple operation,few parameters to be adjusted,easy to implement and so on,and has attracted more and more scholars' attention and is widely used in production and life etc.By analyzing the influence of initial population and important parameters on the performance of firefly algorithm,this paper puts forward the improved firefly algorithm and applies it to the problem of pressure vessel.The main content of the thesis is as follows:(1)The paper introduces the current research status of firefly algorithm,and introduces the basic theory,mathematical model and algorithm flow of firefly algorithm.(2)By analyzing the effect of the initial population on the performance of the algorithm,the cuckoo initialization of firefly algorithm(CSFA)is proposed.The initial population of fireflies is optimized using the cuckoo algorithm to speed up the convergence of the fireflies to the optimal solution.The CSFA algorithm is validated through the test function,verify the effectiveness of the algorithm.(3)The relationship between heuristic algorithm parameter setting and algorithm performance is analyzed.A particle swarm optimization method based on particle swarm optimization is proposed to adaptively select the firefly algorithm parameter values for different optimization problems.Finally,the experimental results show that the particle swarm-firefly algorithm parameters optimization strategy has a strong flexibility and adaptability,and then verify the feasibility and effectiveness of the optimization program.(4)Based on the design problem of pressure vessel and the characteristics of the firefly algorithm,the CSFA algorithm is used to solve the design problem of pressure vessel.The experimental results show that the improved algorithm has better performance.