Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models
Publication: Journal of Water Resources Planning and Management
Volume 132, Issue 4
Abstract
We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal characteristics of contamination events and their impacts. Typical network water quality simulations track contaminant concentration and movement over time, computing contaminant concentration time series for each junction. Given this information, we can compute the impact of a contamination event over time and determine affected locations. This process quantifies the benefits of sensing contamination at different junctions in the network. Ours is the first MIP model to base sensor placement decisions on such data, compromising over many individual contamination events. The MIP formulation is mathematically equivalent to the well-known -median facility location problem. We can exploit this structure to solve the MIP exactly or to approximately solve the problem with provable quality for large-scale problems.
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Acknowledgments
The writers thank Phil Meyers at Pacific Northwest National Laboratory for noting that DSP is equivalent to the -median facility location problem. Sandia is a multipurpose laboratory operated by Sandia Corporation, a Lockheed–Martin Company, for the U.S. Department of Energy under Contract No. DOEDE-AC04-94AL85000.
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© 2006 ASCE.
History
Received: Aug 23, 2005
Accepted: Dec 30, 2005
Published online: Jul 1, 2006
Published in print: Jul 2006
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