This paper analyzes the Steiner-Weber-Problem with piecewise linear or piecewise constant transportation costs. These non-differentiable cost functions are analyzed using different one-step and dynamic linearization methods, which are based on approximations via average and marginal costs. An extensive numerical study compares these approaches with solutions based on linear and geometric regressions of the cost functions. In the numerical examples the dynamic linearization approaches give results near the optimal solutions. The relative deviations of the transportation costs of the approximated solutions to the minimal costs depend on the initialization of the dynamic approaches and improve as the number of demand points increases.