Assessment of the Replicate Compression Heuristic to Improve Efficiency of Urban Water Supply Headworks Optimization
Publication: Journal of Water Resources Planning and Management
Volume 135, Issue 6
Abstract
Urban water supply headworks systems are usually designed to provide high security against drought. The best way to evaluate this security is to use Monte Carlo simulation which is computationally expensive. The advent of parallel computing technology in conjunction with genetic algorithms has made it practicable to optimize operation for drought security. Nonetheless, computation turnaround times remain long. This paper presents a simple heuristic called replicate compression to improve Monte Carlo efficiency. It exploits the well known concept of a critical period. In a high reliability system there should be few critical periods. Therefore, restricting simulation to such periods should bring about substantial savings in computational effort. It was found for problems where the objective function evaluation is only affected by what happens during critical periods, replicate compression provides an effective means for substantially reducing simulation effort. The case study involving a nine-reservoir urban headworks system showed the actual reduction in effort depended on the stress experienced by the system, which in turn affected the frequency of critical periods. Even when the objective function is affected by decisions outside the critical period, replicate compression may provide a useful result by helping to guide the specification of a reduced search space for the genetic algorithm. This strategy can bring about substantial savings in turnaround time.
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Acknowledgments
The Sydney Catchment Authority is thanked for providing information about the Sydney headworks system. The writers bear sole responsibility for the case study.
References
Cui, L., and Kuczera, G. (2003). “Optimization of urban water supply headworks using probabilistic search methods.” J. Water Resour. Plann. Manage., 129(5), 380–387.
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© 2009 ASCE.
History
Received: Sep 6, 2007
Accepted: Feb 18, 2009
Published online: Oct 15, 2009
Published in print: Nov 2009
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