In the water distribution networks, a deliberate or accidental contamination causes loss of water quality; the implementation of a real-time sensor network is essential to promptly detect the event of contamination. To achieve the optimum positioning of the probes, to reduce the cost of the instrumentation and maintenance, and obtaining, at the same time, a reliable monitoring of the system, optimization techniques are widely applied. In the present study, a numerical optimisation approach was compared with the results of an experimental campaign. The optimization problem is formulated in accordance with literature state- of-the-art, using the genetic algorithm NSGA-II coupled with a hydraulic simulator. The results were tested and verified using a looped laboratory distribution network, equipped with a real-time monitoring water quality system, which allows to run contamination experiments in a controlled environment.