Multi-objective Optimization for Monitoring Sensor Placement in Water Distribution Systems

As water distribution systems are vulnerable to a variety of accidental or deliberate contaminant intrusion events, efficient in-situ water quality monitoring is important in providing a robust water supply. To identify optimal placements of monitoring sensors in water distribution systems, a multiple-objective optimization method employing genetic algorithms (GA) in conjunction with data mining, is developed. The proposed methodology is capable of identifying an optimal set of monitoring stations based on three objectives: detection delay time, detection probability, and the affected population prior to detection. To apply the method, a database which stores data for intrusion events at each node, and the classified consequences of these intrusions at each node, is prepared. The initial solutions for multi-objective optimization are obtained from the database based on sensor coverage criteria. Pareto ranking is performed during the GA optimization. The effectiveness of the proposed method is illustrated by applying the methodology to the two networks, Networks 1 and 2, provided by the Battle of the Water Sensor Networks design competition. The final results in application to Networks 1 and 2 are also provided. This paper was presented at the 8th Annual Water Distribution Systems Analysis Symposium which was held with the generous support of Awwa Research Foundation (AwwaRF).