Geodetic networks are very important tools used to monitor earth and/or structural deformations.
However, a geodetic network must be designed to meet sufficiently some network quality
requirements such as precision, reliability, or sensitivity. This is the subject of geodetic network
optimization. The determination of the observation weights problem in the deformation monitoring
networks can be dealt with as an optimization procedure, this problem can performed by solving
the second-order design (SOD) problem. Traditional methods have been used for geodetic
optimization tasks. On the other hand, some heuristic techniques have been started to be used
recently in geodetic science such as the Particle Swarm Optimization (PSO) algorithm. The
general purpose optimization method known as Particle Swarm Optimization (PSO) has received
much attention in past years, with many attempts to find the variant that performs best on a wide
variety of optimization problems.
In this paper, the PSO algorithm, a stochastic global optimization method, has been employed for
the determination of the optimum observation weights to be measured in the field that will meet
the postulated criterion matrix at a reasonable precision. The fundamentals of the method and a
numeric example are given.