Research On Improvement Of Crow Search Algorithm And Its Application

As a new type of swarm intelligence algorithm,the crow search algorithm has the advantages of simple structure,few control parameters,easy to understand and implement,but it also has disadvantages such as slow convergence speed,low optimization precision and blind position update.This thesis analyzes and improves the deficiencies of the crow search algorithm,and uses the improved algorithm for practical optimization problems.The purpose is to further improve the theoretical basis of the crow search algorithm and broaden its application range.The research content of this thesis mainly includes the following three aspects:(1)In order to balance the exploration and development capabilities of the crow search algorithm and improve the optimization accuracy of the algorithm,an adaptive awareness probability operator and a cross-pollination strategy with Cauchy variation are introduced,a crow search algorithm based on flower pollination is proposed.In order to verify its performance,the improved algorithm was used for 20 benchmark functions to test and solve the minimum spanning tree problem,and compared with other meta-heuristic algorithms.Experimental results show that the improved algorithm has strong competitiveness in function optimization and minimum spanning tree problems.(2)In order to speed up the convergence speed of the crow search algorithm and overcome the lack of blindness in its position update,the Jaya algorithm,Gaussian mutation optimization global optimal individual strategy and adaptive flight step operator are introduced,an adaptive crow search algorithm with jaya algorithm and gaussian mutation is proposed.The experimental results of 6engineering examples show that compared with other similar algorithms,the improved algorithm can solve this kind of problems better,and the overall performance is good.(3)In order to broaden the application range of the crow search algorithm,the optimal individual operator is introduced,an improved crow search algorithm is proposed and used to solve the path planning problem of 3D UAV.The experimental results show that,compared with the other five algorithms,the proposed algorithm can solve the 3D UAV path planning problem better.