The monitoring of water distribution systems (WDSs) has been a very popular subject of study since the terrorist attacks of September 11, 2001, and the subsequent passing of laws motivating the study of WDS monitoring to provide system protection in the event of a terrorist attack. Inhibiting many WDS monitoring studies to date is the large amount of computational expense required to conduct meaningful studies, especially for larger WDSs that are of most interest. In this study, methods were developed to determine the "importance" of WDS nodes in being considered as locations for sensors used to monitor a WDS in order to make sensor placement optimization more efficient. Single-objective protection goals considered individually in optimization were maximizing detection likelihood, minimizing expected detection time, and minimizing expected contaminated demand volume. A multiobjective protection goal accounting for all three single-objective goals concurrently was also considered; the formulation of the multiobjective optimization problem was intended to minimize tradeoffs among individual protection goals. Sensor placement optimization was carried out with the Iterative Subset Search Method (ISSM) employing genetic algorithms developed in this work; ISSM used nodal importance rankings to search a small subset of nodes for the optimal solution initially then broadened the search incrementally until convergence to a best solution occurred. To demonstrate the effectiveness of the methods developed, sensor placement was performed according to each of the protection goals for three study systems--one small and two large--and a variety of attack conditions. Desirable sensor node solutions that provided for significant protection were found in all cases, and in many cases sensor placement results were comparable to or better than those of other works. Nodal importance narrowed the search for optimal sensor nodes to a relatively small proportion of WDS nodes in most cases.