Particle Swarm Optimization Algorithms for Optimal Scheduling of Water Supply Systems

In the past decade, evolutionary methods have been used by various researchers to tackle optimal design problems for water supply systems (WSS). In this paper, a optimal operation model with multi-objective mixed discrete variables is established for large-scale water supply systems of some city, and the model is solved by using particle swarm optimization (PSO). Simulation results of the water supply network are compared with those given by using genetic algorithms (GA) to solve the same problem under the same conditions, showing better performance. PSO is shown to be a promising method to solve optimal design problems regarding, in particular, water supply systems, according to the results herein obtained.