Mathematical based decision support for operative scheduling in water supply systems is highly desirable but leads very often to very difficult optimization problems. In this paper we propose a nonlinear programming approach that yields practically satisfactory operating schedules in acceptable computing time even for large system with several pumps. Based on a carefully designed software using Scatter Search, Tabu and Neural Networks in hybrid optimization algorithms, this approach employs a special initialization strategy for convergence acceleration, special minimum up and down time constraints together with pump aggregation to handle switching decisions, techniques for further speed-up. Results for selected application scenarios at Bouregreg water production system in Morocco demonstrate the high performance of the approach. © 2010 ASCE.