Research On Improved Flower Pollination Algorithm Based On SQP Local Search

Flowers pollinate algorithm is new type of swarm intelligence optimization algorithm,which is proposed by Yang of the University of Cambridge new swarm intelligence optimization algorithm.The algorithm has been successfully applied in the layout of the sensors,energy hybrid system of wind power grid and other.This paper will improve the performance of flower pollination method.It is proposed based on linear decreasing inertia parameters of flowers to pollinate optimization algorithm,improved the flowers to pollinate optimization algorithm to convert probability P in the initial set is fixed,not flexible conversion of global search and local search mode problem.Because flowers pollinate algorithm's local search ability is not strong,its inaccurate precision and the premature convergence issue,and so on.An improved flower pollination algorithm integrated with sequential quadratic programming local search is proposed.Improved algorithm uses SQP local search,in the later time of this algorithm,slow iterative phenomenon appears,the best individual used SQP local search to overcome the slow convergence rate of the flower pollination optimization algorithm,and to jump out of the local optimal traps,the best individual is used Cauchy mutation operation to improve global searching ability of the algorithm?...