Abstract
The application of Information and Communication Technologies (ICT) for water supply systems has steadily increased in the
last 20 years. The city of Milan is presented as case study where the main challenge for the coming 20 years is the efficient use of
energy. Opposite to other parts of the world, in Milan, water is neither scarce nor there is a growing need for supply. Given that
the system completely relies on pumping, optimization algorithms and sensor technologies can be applied to reduce energy
consumption. This article presents research in optimization for Pump Scheduling (PS), carried out under the framework of the
ICeWater project (funded by EU-FP7). For this purpose approaches using two multi-objective optimization algorithms (Nondominated
Sorting Genetic Algorithm - NSGA-II and Archive based Micro-Genetic Algorithm - AMGA2) have been applied.
The results indicate that a tangible energy consumption reduction can be achieved by using pump scheduling optimization.