Optimal Sampling Design Methodologies for Water Distribution Model Calibration
Publication: Journal of Hydraulic Engineering
Volume 131, Issue 3
Abstract
Sampling design (SD) for water distribution systems (WDS) is an important issue, previously addressed by various researchers and practitioners. Generally, SD has one of several purposes. The aim of the methodologies developed and presented here is to find the optimal set of network locations for pressure loggers, which will be used to collect data for the calibration of a WDS model. First, existing SD approaches for WDS are reviewed. Then SD is formulated as a multiobjective optimization problem. Two SD models are developed to solve this problem, both using genetic algorithms (GA) as search engines. The first model is based on a single-objective GA (SOGA) approach in which two objectives are combined into one using appropriate weights. The second model uses a multiobjective GA (MOGA) approach based on Pareto ranking. Both SD models are applied to two case studies (literature and real-life problems). The results show several advantages and one disadvantage of the MOGA model when compared to SOGA. A comparison of the MOGA SD model solution to the results of several published SD models shows that the Pareto optimal front obtained using MOGA acts as an envelope to the Pareto fronts obtained using previously published SD models.
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Acknowledgment
Results presented in this paper were obtained within a research project under the United Kingdom Engineering and Physical Sciences Research Council Grant No. GR/M66981/01, which is gratefully acknowledged.
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© 2005 ASCE.
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Received: Jun 4, 2003
Accepted: Mar 26, 2004
Published online: Mar 1, 2005
Published in print: Mar 2005
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