Minimizing the consequences of intentional attack on water infrastructure

Since September 11, 2001, protecting the water infrastructure of the USA and improving water network resiliency have become priorities in the US water industry. In this work, we develop methods to mitigate the consequences of water shortage resulting from destruction of facilities in water networks. These methods integrate search techniques, such as branch-and-bound and genetic algorithms, with a hydraulic solver to check demand feasibilities across a residual water network. The objective is to identify a feasible customer demand pattern that minimizes the consequences of water shortage in the downgraded network. We present a mathematical model of the problem addressed along with an exact solution methodology and several heuristics. We apply these methodologies to three water networks ranging in size from approximately 10–700 nodes and compare the solution quality and computational efficiency.