Journal of Theoretical
and Applied Mechanics
55, 3, pp. 801-812, Warsaw 2017
DOI: 10.15632/jtam-pl.55.3.801
and Applied Mechanics
55, 3, pp. 801-812, Warsaw 2017
DOI: 10.15632/jtam-pl.55.3.801
Surface-to-air missile path planning using genetic and PSO algorithms
Optimization algorithms use various mathematical and logical methods to find optimal points.
Given the complexity of models and design levels, this paper proposes a heuristic optimization
model for surface-to-air missile path planning in order to achieve the maximum
range and optimal height based on 3DOF simulation. The proposed optimization model involves
design variables based on the pitch programming and initial pitch angle (boost angle).
In this optimization model, we used genetic and particle swarm optimization (PSO) algorithms.
Simulation results indicated that the genetic algorithm was closer to reality but took
longer computation time. PSO algorithm offered acceptable results and shorter computation
time, so it was found to be more efficient in the surface-to-air missile path planning.
Given the complexity of models and design levels, this paper proposes a heuristic optimization
model for surface-to-air missile path planning in order to achieve the maximum
range and optimal height based on 3DOF simulation. The proposed optimization model involves
design variables based on the pitch programming and initial pitch angle (boost angle).
In this optimization model, we used genetic and particle swarm optimization (PSO) algorithms.
Simulation results indicated that the genetic algorithm was closer to reality but took
longer computation time. PSO algorithm offered acceptable results and shorter computation
time, so it was found to be more efficient in the surface-to-air missile path planning.
Keywords: path planning, genetic algorithm, PSO algorithm, surface-to-air missile; 3DOF simulation