Adelaide Research and Scholarship : Schools and Disciplines : School of Civil, Environmental and Mining Engineering : Civil and Environmental Engineering Publications

Type:	Conference paper
Title:	Improving metamodel-based optimization of water distribution systems with local search
Author:	Broad, Darren Dandy, Graeme C. Maier, Holger R. Nixon, J. B.
Citation:	IEEE Congress on Evolutionary Computation, 16-21 July, 2006:pp.710-717
Publisher:	IEEE
Issue Date:	2006
ISBN:	0780394879
Conference Name:	IEEE Congress on Evolutionary Computation (2006 : Vancouver, B.C.) CEC 2006
School/Discipline:	School of Civil and Environmental Engineering
Abstract:	Metamodels can be used to aid in improving the efficiency of computationally expensive optimization algorithms in a variety of applications, including water distribution system (WDS) design and operation. Genetic Algorithm (GA)-based optimization of WDSs is very computationally expensive to optimize a system in a practical amount of time for real-sized problems. A metamodel, of which Artificial Neural Networks (ANNs) are an example, is a model of a complex simulation model. It can be used in place of the simulation model where repeated use is necessary, such as when carrying out GA optimization. To complement the ANN-GA, six local search algorithms have been developed or applied in this research, with the aim of improving the performance of metamodel-based optimization of WDSs. All algorithms performed well, however, using computational intensity as a criterion with which to evaluate results, the best local search algorithms were Sequential Downward Mutation (SDM) and Maximum Savings Downward Mutation (MSDM).
Description:	Copyright 2006 IEEE
RMID:	0020062796
DOI:	10.1109/CEC.2006.1688381
Links to content (authorised users):	Check full text options http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1688381
Appears in Collections:	Civil and Environmental Engineering Publications
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