Comparison of PSO, GAs and Analytical Techniques in Second-Order Design of Deformation Monitoring Networks

摘要

Deformation monitoring is a kind of continuous recording positions (horizontal and vertical coordinates) precisely regardless the deformation pattern and instrument used. In general, a deformation monitoring network can be designed using the trial and error method or analytical methods such as linear programming and nonlinear programming. Recently, a deformation monitoring network may also be designed by heuristic optimization algorithms such as Genetic Algorithms (GAs), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). In this paper, GAs and PSO, which are heuristic optimization techniques, are applied to a geodetic horizontal deformation monitoring networks to solve second-order design problem. The results proved that both GAs and PSO can be used as alternative methods in place of the traditional optimization techniques with high efficiency.