Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach

This paper examines the application of a particle filtering-based optimization technique, the genealogical decision trees (GDT), to a finite horizon pump scheduling problem in a water distribution network. The GDT approach for trajectory tracking is first introduced, and a modified algorithm for minimization of costs during pump sequence optimization is then presented. Several variants of the algorithm are suggested, using the extended end constraint and neutrality. The performance of the optimization in various algorithm and parameter settings is examined in extensive simulations. It was observed that both the extended end constraint and neutrality improved the performance, however the deviation between solutions within a population and between different runs remained uncomfortably large. Finally, a comparison with a number of alternative up-to-date optimization techniques is provided. It was observed that the performance of GDT was adequate, compared with the best available approaches.