Particle swarm optimization compared to other heuristic search techniques for pipe sizing

An economical design of water distribution network is the aim of any agency dealing with water supply distribution. The fund needed for the construction, maintenance and operations of these systems requires an achievement of a good compromise between technical and economical aspects. Though the overall planning process of water distribution networks consists of three phases: layout, design and operation and each phase is not independent, but from a technical point of view, each can be formulated and solved as a separate problem. Several methods are available for designing a water distribution network. In the present research, optimal design of water distribution network is experimented with particle swarm optimization (PSO) under dynamic adaptation and it is compared with genetic and simulated annealing algorithm. Particle swarm optimization is a relatively new generation of combinatorial meta-heuristic evolutionary algorithm that utilizes the swarm intelligence to achieve the goal of optimizing a specified objective function. This algorithm uses the cognition of the individuals and social behavior in the optimization process. The effectiveness of this algorithm is reported in terms of number of function evaluations and CPU time.