Water distribution networks design belongs to a class of large combinatorial nonlinear optimization problems, involving complex implicit constraints, such as conservation of mass and energy equations, which are commonly satisfied by using hydraulic simulation solvers. Recently, many researchers have shifted the focus of traditional optimization methods to the use of metaheuristic approaches for handling this complexity. Particle swarm optimization (PSO) is one of the evolutionary algorithms which was developed for optimization problems with continuous variables. Also it has been adapted successfully in other problems contexts with discrete variables. In this research, a simple modified particle swarm optimization (SMPSO) was applied to minimize water distribution networks cost. The SMPSO was used as novel factor to decrease inertia weight linearly with time for each iteration to facilitate the balance of global and local researches. The SMPSO algorithm was linked to a hydraulic simulator, EPANET 2.0. This approach was applied to three benchmark in water distribution network optimization problems. The results indicate that a significant improvement in performance of PSO could be achieved by decreasing inertia weight over the iterations.

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