  Drinking water for human health and well-being is crucial. Accidental and
intentional water contamination can pose great danger to consumers. Optimal
design of a system that can quickly detect the presence of contamination in a
water distribution network is very challenging for technical and operational
reasons. However, on the one hand improvement in chemical and biological sensor
technology has created the possibility of designing efficient contamination
detection systems. On the other hand, methods and tools from complex network
theory, which was primarily the domain of mathematicians and physicists,
provide analytical output for engineers to design, optimize, operate, and
maintain complex network systems such as power grids, water distribution
networks, telecommunication systems, internet, roads, supply chains, traffic
and transportation systems. In this work, we develop a new modeling approach
for the optimal placement of sensors for contamination detection in a water
distribution network. The approach originally combines classical optimization
and complex systems theory.
