Application Of Improved Particle Swarm Optimization Algorithm In Route Planning

Route planning is the core technology of mission planning system. Route planningtechnology has got great progress in recent years, has been widely used in navigationsystems of Unmanned Aerial Vehicle, Submarines, and ships, etc. UAV route planningtechnology aims to find an optimal or sub-optimal trajectory for aircraft while considersthe constraints of vehicle itself and environmental factors.Particle swarm optimization algorithm is applied to route planning problem and isimproved according to the characteristics and needs of route planning problem in thispaper. The main content is:(1) particle swarm optimization algorithm with variabilityfactor is applied in local planning of hierarchical route planning;(2) route planning baseon multi-objective particle swarm optimization algorithm.To reduce the complexity of time and space of problem and improve efficiency ofpath planning, route planning use hierarchical planning strategy to deal with differentconstraints separately during the planning process. This paper proposes an improvedmethod on basis of particle swarm optimization algorithm, introducing a variation factorinto PSO algorithm. The improved algorithm designs a specific perturbation operator toenhance its search ability while avoiding premature convergence of PSO algorithm.Simulation results show that the improved method can searches excellent feasible tracksquickly and enhances planning efficiency effectively.Route planning has to consider various constraints, and most of its objectives areconflicting. Route planning is complex multi-objective optimization problem. This paperimprove particle swarm optimization algorithm base on multi-objective optimizationtheory, proposing multi-objective particle swarm optimization algorithm and developinga multi-objective optimization strategy. The strategy defines sub objectives for routeplanning by analyzing the constraints of problems and uses multi-objective particle swarm algorithm to deal with route planning problems, searching for Pareto optimalsolution set for decision-marking. Finally, simulation experiments have verified thefeasibility of the new method.