This thesis addresses the selection of target sets to disrupt an adversary's logistics network. In the presence of many objectives-such as reducing maximum flow, lengthening routes, avoiding collateral damage, all at minimal risk to our pilots-the problem of determining the best target set is complex. Previous efforts have not adequately considered the value of the remaining network functionality after target destruction. In addition, current network targeting procedures optimize a single metric. This thesis uses a multi-objective decision analysis framework capturing actual targeting decision-maker values and preferences to evaluate and analyze ten alternative target sets. Sensitivity analysis and persistency analysis on the results give insight as to how to select better target sets to meet stated strategic objectives.