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This paper proposes an optimization algorithm that is suitable for choosing the optimal number and position of the measurement devices in distribution state estimation (DSE) procedures used in modern electric distribution networks. The algorithm is based on the techniques of dynamic programming, and its goal is to guarantee both the minimum cost and the accuracy required for the measured data needed to operate management and control issues, such as energy dispatch and protection coordination. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. The aggregation of the quantities to be measured in a few measurement points has been favored to reduce the overall cost of the measurement system. Random changes in the loads are considered to establish adequate reference conditions for the tests. Tests relevant to real distribution networks are presented to show the validity of the proposed approach. The results emphasize how both the influence of the tolerance on the network parameters and the cost of the measurement system can dramatically be minimized by suitably choosing the algorithm to be implemented to solve the DSE problem.