Plan Research on a New Heuristic PSO to Solving Urban Optimal Path
FANG Xin
Abstract：Aiming at the shortcomings of particle swarm optimization and poor local optimization ability,grid method with bi-nary information is used to model the environment.Combined with improved A*algorithm to initialize the particle group,improved PSO algorithm is proposed based on map data which mathematical model to derive the algorithmic environment model.The algorithm considers the collision avoidance constraint,the motion constraint and the distance constraint. The new heuristic function and the nonlinear dynamic adjustment are used to study inertia weight.Based on the path length,the concept of smoothness is introduced to find the optimal path.Compared with algorithms,the experimental results show that proposed model and improved algorithm can ef-fectively avoid obstacles,search the optimal path,reduce the running time,improve convergence rate and search ability of the algo-rithm.
Keywords：optimal pathheuristic functionPSO algorithminertia weight
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 270-275 )