Abstract
The optimization of looped water distribution systems is a complex problem as the pipe flows are unknown variables. Although 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, 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. The aim of this paper is to evaluate the performance of several meta-heuristic techniques: genetic algorithms, simulated annealing, tabu search, and iterated local search. These techniques were first validated and compared by applying them to a medium-sized benchmark network previously reported in the literature. They were then applied to a large irrigation water distribution network that has been proposed in a previous work to assess their performance in a practical application. All the methods tested performed adequately well, compared with the results found in previous works. Genetic algorithm was more efficient when dealing with a medium-sized network, but other methods outperformed it when dealing with a real complex one.
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Reca, J., Martínez, J., Gil, C. et al. Application of Several Meta-Heuristic Techniques to the Optimization of Real Looped Water Distribution Networks. Water Resour Manage 22, 1367–1379 (2008). https://doi.org/10.1007/s11269-007-9230-8
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DOI: https://doi.org/10.1007/s11269-007-9230-8