COMPARISON BETWEEN THE GENETIC ALGORITHMS OPTIMIZATION AND PARTICLE SWARM OPTIMIZATION FOR DESIGN THE CLOSE RANGE PHOTOGRAMMETRY NETWORK

Close range photogrammetry network design is referred to the process of placing a set of cameras in order to achieve photogrammetric tasks. The main objective of this paper is tried to find the best location of two/three camera stations. The genetic algorithm optimization and Particle Swarm Optimization are developed to determine the optimal camera stations for computing the three dimensional coordinates. In this research, a mathe matical model representing the genetic algorithm optimization and Particle Swarm Optimization for the close range photogrammetry network is developed. This paper gives also the sequence of the field operations and computational steps for this task. A test field is included to reinforce the the oretical aspects.