Pumping stations used in water distribution networks (WDNs) consume a significant portion of the energy required to deliver municipal drinking water. Smart management strategies such as optimal pump scheduling (OPS) have gained the attention of water companies and managing authorities because they help reduce both energy costs and detrimental consequences for the environment. Genetic algorithms (GAs) are frequently used to approximate the solution of OPS problems, although many researchers have resorted to hybrid models to improve computational performance. This paper shows that despite the lack of support in the literature, a well-designed GA is capable of tackling OPS problems effortlessly. In addition, a new decision-variable representation is proposed, specifically suited to parallel pump systems, which is able to further improve the performance of a GA. Finally, the outperforming capabilities of the new variable representation are demonstrated with two case studies from recent literature.

The present work describes a procedure for the evaluation of the optimal number, position, configuration, and sizes of detention tanks in urban drainage networks, to decrease the maximum flow depths and velocities for an assigned return period and to comply with the local design requirements. Each candidate solution of the optimization problem is evaluated by means of a semidistributed hydrological model in which the kinematic wave is used as flood routing model, whereas the variational approach is used to evaluate the critical flow characteristics corresponding to a given return period. The procedure, which makes use of a genetic algorithm to search for the optimal solution among the candidates, is applied to a case study drainage network, considering superpipe-based detention tanks as detention systems. The results indicate that these tanks are effective in the rehabilitation of the drainage network and that the cost of this intervention is substantially lower than that corresponding to the upgrading of existing pipes

Water loss is a phenomenon frequently observed within water distribution systems (WDSs), that is considerably worsened by an excessive pressure throughout the network. As an alternative option to pipe replacement, the use of pumps working as turbines, throttle control valves (TCVs), or pressure reduction valves (PRVs) can be used to reduce leakage. For a preassigned number of these devices, their positions and settings can be chosen to minimize the water losses in the network or to minimise the costs associated with the leakage. On the other hand, for a preassigned reduction in leakage, the number, the position and the setting of valves could be optimized in order to minimize their installation and maintenance costs. Based on these observations, a procedure for the optimal choice of the number, position and setting of PRVs is devised. The procedure is aimed at reducing the whole cost associated with water loss in urban WDSs, due to the background leakage from joints, and the purchase, installation and maintaining of the PRVs themselves. The effectiveness of the procedure, which is based on the physical modelling of leakage from pipe joints as well as on the use of a genetic algorithm, is proven using a small but realistic example.