Research On Multi-strategy Hybrid Artifical Electric Field Algorithm And Application

Artificial electric field algorithm(AEFA)is a meta-heuristic optimization algorithm based on Coulomb's law of electrostatic force.The algorithm has the advantages of fewer parameters,fast convergence,strong exploration ability and small computational complexity,and shows excellent performance in nonlinear unconstrained optimization problems.With the deepening of the research,researchers found that artificial electric field algorithm also has some shortcomings,such as easy to fall into local optimal,low population diversity,insufficient exploration ability and so on.In this paper,based on the performance analysis of the basic artificial electric field algorithm,aiming at the shortcomings of the artificial electric field algorithm,different evolution strategies are added to improve its optimization accuracy and speed.The aim is to improve the performance of artificial electric field algorithm and broaden its application range.The main research work of this paper is as follows:(1)To solve the problem of truss structure optimization,the artificial electric field algorithm is simplified(SAEFA)by electrostatic attraction and introduced electrostatic repulsive force.Some classical and the latest meta-heuristic algorithms are selected for performance comparison.The simulation results show that the simplified artificial electric field algorithm has remarkable performance in solving truss structure optimization problems.(2)To solve the problem that the artificial electric field algorithm is easy to fall into local optimum,the population diversity is not high,and the exploration ability is not enough,an artificial electric field algorithm with inertia mechanism and repulsion force is proposed(IRAEFA),so as to improve the population diversity and exploration ability of the algorithm and speed up the convergence of the algorithm.The improved algorithm is applied to solve the spherical minimum spanning tree problem,and the performance of the algorithm is tested by setting problems of different dimensions,and the test results are compared with other algorithms.The results show that the improved algorithm is better than other algorithms in solving the spherical minimum spanning tree problem.(3)In order to broaden the application field of artificial electric field algorithm,the artificial electric field algorithm with inertia and repulsion force is applied to solve the multi-platform earth coverage observation problem.Compared with GA and AEFA,the results show that IRAEFA also has excellent performance in this problem.(4)To improve the local development ability of the artificial electric field algorithm,the state transfer strategy was introduced to propose the artificial electric field algorithm based on greedy state transfer(GSTAEFA),and the improved artificial electric field algorithm was applied to solve the spherical multi-traveling salesman problem.Compared with other algorithms,the experimental results show that the development ability of the algorithm is enhanced.