Three-dimensional (3D) measurements can be recovered from several views by triangulation. This paper deals with the problem of where to place the cameras in order to obtain a minimal error in the 3D measurements, also called camera network design in photogrammetry. We pose the problem in terms of an optimization design, dividing it into two main components: (1) an analytical part dedicated to the analysis of error propagation from which a criterion is derived, and (2) a global optimization process to minimize this criterion. In this way, the approach consists of an uncertainty analysis applied to the reconstruction process from which a covariance matrix is computed. This matrix represents the uncertainty of the detection from which the criterion is derived. Moreover, the optimization has discontinuities due to the presence of occluding surfaces between the viewpoint and the object point group, which leads to a combinatorial optimization process. These aspects are solved using a multi-cellular genetic algorithm. Experimental results are provided to illustrate the effectiveness and efficiency of the solution.