Improvement And Application Of Coyote Optimization Algorithm

The coyote optimization algorithm is an intelligent optimization algorithm proposed by simulating the living phenomenon of coyotes living in packs.This algorithm proposes a new algorithm design that balances exploration and mining performance.It has the advantages of clear structure and easy application,but it has disadvantages such as poor global search performance and low convergence accuracy.Based on the study and research of the coyote optimization algorithm,this thesis proposes some improvement measures for the shortcomings of the algorithm,and expands the application field of the algorithm.The main research contents are as follows:(1)In order to improve the global search performance of the algorithm,the algorithm was improved by introducing a deformed elite retention strategy,adding environmental impact factor in the growth process of coyotes,and substituting the grown coyotes into the Kent map to traverse the search space.The improved algorithm is applied to the constructed bi-level programming model for the location and capacity of electric vehicle charging stations.The calculation example shows that the constructed model and the improved algorithm are effective.(2)In order to calculate the numerical solution of the multi-integral more efficiently and accurately,the calculation problem of the numerical solution of the multi-integral is transformed into an optimization problem that can be solved by intelligent optimization algorithm,and the adaptive coyote optimization algorithm is obtained by introducing strategies such as the adaptive growth operator to improve the coyote optimization algorithm.Numerical examples show that the optimization model and the adaptive coyote optimization algorithm for calculating the multi-integral numerical solution are effective.(3)In order to ensure the efficiency of emergency rescue,constructing a satisfaction emergency material scheduling model;the update formula of the firefly algorithm is introduced to perturb the group optimal coyote,and added the solution update coefficient of the equilibrium optimizer combined with the global optimal coyote update growth mechanism,at the same time,adjusted the choice of being expelled and accepted by the group,the firefly coyote optimization algorithm is obtained.The firefly coyote optimization algorithm is applied to the constructed emergency material scheduling model,which reflects the effectiveness of the algorithm and model.