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Hybrid Genetic Algorithms for Multi-Objective Optimisation of Water Distribution Networks
Edward Keedwell and Soon-Thiam Khu
Centre for Water Systems, School of Engineering and Computer Science and Mathematics, University of Exeter, North Park Road, Exeter, UKE.C.Keedwell@exeter.ac.uk
S.T.Khu@exeter.ac.uk
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.
LNCS 3103, p. 1042 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004