Pareto Optimality for Sensor Placements in a Water Distribution System

As society looks to provide the most effective identification of possible intrusion events, issues of sensor placement in water distribution systems are drawing increased attention. A multiple objective optimization problem with two competitive objectives is formulated herein: (1) minimize time delay, and (2) maximize sensor detection redundancy. The two objectives are evaluated, based on a prebuilt database containing the array of potential intrusion events and detection information. Pareto fronts are developed to assess impacts of increasing numbers of sensors by nondominated genetic algorithm-II (NSGA-II). Further, Pareto front performance improvement of increasing numbers of sensors is quantified by average normalized Euclidean distance to identify the point of diminishing marginal return aiming to provide rationale for estimating the number of sensors needed for a water distribution system. A case study is conducted for the City of Guelph water distribution system. It is observed that increasing the ...

[1]  Cynthia A. Phillips,et al.  Limited-Memory Techniques for Sensor Placement in Water Distribution Networks , 2008, LION.

[2]  Zoran Kapelan,et al.  Risk-Based Sensor Placement for Contaminant Detection in Water Distribution Systems , 2010 .

[3]  Zheng Yi Wu,et al.  MULTI OBJECTIVE OPTIMIZATION OF SENSOR PLACEMENT IN WATER DISTRIBUTION SYSTEMS , 2008 .

[4]  Zoran Kapelan,et al.  An Efficient Algorithm for Sensor Placement in Water Distribution Systems , 2008 .

[5]  Avi Ostfeld,et al.  Multi-objective Sensor Placements with Improved Water Quality Models in a Network with Multiple Junctions , 2009 .

[6]  Cynthia A. Phillips,et al.  Sensor Placement in Municipal Water Networks with Temporal Integer Programming Models , 2006 .

[7]  Mustafa M. Aral,et al.  Optimization Model and Algorithms for Design of Water Sensor Placement in Water Distribution Systems , 2008 .

[8]  Andreas Krause,et al.  Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks , 2008 .

[9]  Zoran Kapelan,et al.  OPTIMAL SENSOR PLACEMENT FOR THE EFFICIENT CONTAMINANT DETECTION IN WATER DISTRIBUTION SYSTEMS , 2009 .

[10]  Avi Ostfeld,et al.  The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms , 2008 .

[11]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[12]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[13]  Avi Ostfeld,et al.  Optimal Layout of Early Warning Detection Stations for Water Distribution Systems Security , 2004 .

[14]  Edward A. McBean,et al.  Multi-Objective Optimization for Monitoring Sensor Placement in Water Distribution Systems , 2008 .

[15]  Edward A. McBean,et al.  Multi-stage response to contaminant ingress into water distribution systems and probability quantification , 2009 .

[16]  DebK.,et al.  A fast and elitist multiobjective genetic algorithm , 2002 .

[17]  Avi Ostfeld,et al.  Sensor Network Design Proposal for the Battle of the Water Sensor Networks (BWSN) , 2008 .

[18]  Avi Ostfeld,et al.  Multiobjective Contaminant Sensor Network Design for Water Distribution Systems , 2008 .