A memetic algorithm applied to the design of water distribution networks

The optimal design of water distribution networks is a real optimization problem that consists of finding the best way to convey water from the sources to the users, satisfying their requirements. Many researchers have reported algorithms for minimizing the network cost applying a large variety of techniques, such as linear programming, non-linear programming, global optimization methods and meta-heuristic approaches. However, a totally satisfactory and efficient method is not available as yet. Many works have assessed the performance of these techniques using small or medium-sized benchmark networks proposed in the literature, but few of them have tested these methods with large-scale real networks. This paper introduces a new memetic algorithm for the optimal design of water distribution networks. In order to establish an accurate conclusion, five other approaches have also been adapted, namely simulated annealing, mixed simulated annealing and tabu search, scatter search, genetic algorithms and binary linear integer programming. The results obtained in three water distribution networks show that the memetic algorithm performs better than the other methods, especially when the size of the problem increases.