Resilient sensor placement in water distribution networks using multiobjective evolutionary algorithms - Tingzon, Isabelle B.
One of the major challenges in water distribution networks is the large amounts of water losses, called non-revenue water, incurred every year. Water leakages caused by pipe bursts and failures contribute significantly to the problem of water loss. One way to reduce the impact of failure is by installing hydraulic pressure sensors along the network to automate detection of abnormal conditions. However, these sensors are also vulnerable to failure, especially when deployed in hazardous locations or manipulated by an adversary. In this study, we propose a framework for finding an optimal placement of sensors in water distribution networks that is resilient against failures and attacks. We formulated the resilient sensor placement problem as a multi-objective optimization problem and apply Pareto-based multi-objective evolutionary algorithms to optimize several conflicting objectives. Specifically, we applied the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2) to the resilient sensor placement problem. We then evaluated and compared the performance of the sensor placement designs obtained for real water distribution networks in the Metro Manila area. Finally the K-means clustering technique was used to prune the set of Pareto-optimal solutions and obtain a smaller set of representative solutions; thus making it easier for the decision maker to select a final sensor placement design.