Infrastructure system restoration at shortest time became a paramount demand to retain system’s functionality to normal performance and avoid services from being ceased for a long time. Enormous studies elucidated the effect of project planning in the restoration problem, aspect studied as schedule, cost, and quality helped in organizing the efforts to restore disrupted networks efficiently with lowest time and costs. However, urging necessities to expedite system restoration affects the validity of normal restoration plans, post optimization model is needed to compress restoration schedule. Method presented in this work is applying crashing on network restoration as a schedule compression technique, this is attained by allocating more resources to recover the network, thus adding additional costs to restoration activities. Two cases were studied, first is allocating the same available human resources for additional working units, second is allocating external human resources to restore the network, both cases resulted in partial crashing, additional costs, and time reduction. Implications of crashing the network are represented by a cost benefit analysis for a set of solutions, these solutions provide decision makers with the tradeoffs between time and cost to adjust their plans according to project priorities and available budget. Example presented in this work used Shelby County, Tennessee USA data.