Application of particle filter algorithm in nonlinear constraint optimization problems

To overcome the shortcomings of low solution precision of the nonlinear constraint optimization problems, a new optimization algorithm based on the particle filter, which is used to solve nonlinear constraint optimization problems, is brought forward in this paper. And the model and mechanism of particle filter are combined in this optimization algorithm. Firstly, the basic principle of the particle filter algorithm is systematically introduced. Secondly, a new optimization method based on particle filter is enunciated in detail and its design idea and operation steps are given. Moreover, the nonlinear constraint optimization problems are converted into function optimization problems, and a mathematical model of the particle filter optimization algorithm for solving nonlinear constraint optimization problems is established. Finally, the simulation examples are finished to prove the validity of the new algorithm. The simulation results have shown that the new optimization method based on particle filter can solve the nonlinear constraint optimization problems effectively and accurately, which also provides a new method for the nonlinear constraint optimization research.