A simulation-optimization methodology was used to assess monitoring strategies for a drinking water distribution network. Multiple simulation trials of contamination events were used to create input data for an integer optimization problem. A network model, based on the Blacksburg, VA water distribution system, was used as the basis for a case study of contaminant transport under conditions of uncertainty. The model was not calibrated due to the lack of reliable field data. Optimization of monitoring plans was performed within the context event based simulation trials. This precluded the design of monitoring plans that were directly compatible with requirements of water quality regulations. However, the results of the optimization did provide information that may be of use to the broader problem of compliance monitoring. Optimal plans were assessed in comparison with several alternative plans using a separate set of simulation trials. Optimization of monitoring plans derived from simulated source node contamination events was generally effective at choosing points that provided better detection of source node contamination than alternative plans based on random sampling or judgement sampling. Optimal monitoring plans derived from simulated random node contamination events were ineffective at detecting random node contamination. The results of optimization and the separate analysis of monitoring plan performance indicated that the number of simulation trials may have been inadequate to completely describe the stochastic behavior of the system. Additionally, comparison of these results with those obtained from a previous simulation study indicate that the results of any simulation of distribution system contamination may be very sensitive to the level of contaminant loading and the size and layout of the system. / Master of Science