A New Automated Algorithm for Optimization of Measurements for Achieving the Required Accuracy of a Geodetic Network

Abstract

The optimization of measurements in a geodetic network (second-order design) has been investigated in the past; however, the practical usability of the outcomes of most of such studies is doubtful. Hence, we have proposed a new automated optimization algorithm, taking into account the practical aspects of total station measurements. The algorithm consists of four parallel partial algorithms, of which one is subsequently automatically selected—the one meeting the geodetic network accuracy requirements with the lowest number of necessary measurements. We tested the algorithm (and individual partial algorithms) on four geodetic networks designed to resemble real-world networks with 50–500 modifications to each of those networks in individual tests. The results indicate that (i) the results achieved by the combined algorithm are close to the optimal results and (ii) none of the four partial algorithms universally performs the best, implying that the combination of the four partial algorithms is necessary for achieving the best possible results of geodetic network optimization.