Research On Improved Flower Pollination Algorithm And Its Application

The flower pollination algorithm is a newly proposed group intelligence optimization algorithm,which has the characteristics of simple structure and easy implementation.With the continuous development of the theory and application of this algorithm,more and more scholars are keen to improve it and apply it to more fields.Based on the flower pollination algorithm,the principle,difficulties and the problems of the existing algorithm are systematically studied.Combining with the study of the characteristics of other optimization algorithms,two new flower pollination algorithms were proposed and one of them was applied to the engineering example.First,for the problem of small pollination range in the self-pollination link of the basic flower pollination algorithm,a simplified sine and cosine algorithm is embedded,and for the problem of poor optimal accuracy of the cross-pollination link,the elite pollen calculation will be introduced.A flower pollination algorithm combining sine cosine algorithm and elite operator is proposed.Then,ten sets of standard test functions are selected for testing,and the experimental results and iterative images are compared and analyzed with the traditional flower pollination algorithm.The flower pollination algorithm combining sine cosine algorithm and elite operator significantly improves the stability of the algorithm and the accuracy of the optimal value.Secondly,in view of the problem that the flower pollination algorithm is easy to fall into the local optimal value in the cross-pollination link,and the population is not rich enough in the self-pollination link,the improved grasshopper optimization algorithm and the elite pollen operator after mutation and crossover operations are introduced respectively.A flower pollination algorithm based on grasshopper optimization algorithm and elite operator is proposed.The proposed algorithm is mainly to solve the nonlinear constrained optimization problem.Three classic engineering optimization design problems are selected for simulation experiments.The comparison results show that the flower pollination algorithm based on the grasshopper optimization algorithm and elite operator is more precise and universal.