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Schachinger Hartmuth

The Optimization of Geodetic Networks with Simulated Annealing

The optimization of geodetic networks is one of the most difficult tasks for geodesists. It needs much knowledge and experience to design an accurate and reliable network which is easy to measure as well. The process of designing networks has been poorly supported with computers by now. They are mainly used for analyzing the design but are not yet capable for making suggestions to improve the design.

This work shows how to optimize a network automatically. Network design is treated as a combinatory problem. In case of a second order design the optimizing procedure looks for the combination of measurements which fulfills all quality criteria and needs the lowest effort for measuring the network. Therefore the optimization procedure needs to know all possible measurements in the network.

The thesis describes the necessary quality criteria and the cost function for the optimization. The cost function is not smooth and it has many suboptima. Therefore it is not possible to use normal optimization techniques. Here Simulated Annealing (SA) has been used, which can deal with many suboptima and non smooth functions. With SA it is possible to find the optimum of the cost function. To speed up the optimization and save computation time it is not necessary to find the global optimum. It is enough to approximate the optimum with a low suboptimum.

The algorithm for optimization is tested with various examples. The tests show that an optimization is possible. The algorithm proves to be useable in every day geodetic network optimization.

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