Abstract
Genetic algorithms have been a standard technique for engineers optimising water distribution networks for some time. However in recent years there has been an increasing interest in multi-objective genetic algorithms that allow engineers a set of choices when implementing a solution. A choice of solutions is vital to help engineers understand the problem and in real world scenarios where budgets and requirements are flexible. This paper discusses the use of a local search procedure to speed up the convergence of a multiobjective algorithm and reports results on a real water distribution optimisation problems. This increase in efficiency is especially important in the water network optimisation field as the simulation of networks can be prohibitively expensive in computational terms.
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Keedwell, E., Khu, ST. (2004). Hybrid Genetic Algorithms for Multi-Objective Optimisation of Water Distribution Networks. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_115
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DOI: https://doi.org/10.1007/978-3-540-24855-2_115
Publisher Name: Springer, Berlin, Heidelberg
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