This paper presents a stochastic integer program developed to determine how to schedule inspection, damage assessment, and repair tasks so as to optimize the post-earthquake restoration of the electric power system. The objective of the optimization is to minimize the average time each customer is without power, and a genetic algorithm is used to solve it. The effectiveness of the schedules recommended by the optimization are evaluated by running a detailed discrete event simulation model of the restoration process with both the optimization-generated schedules and the power company's original schedules, and comparing the resulting restorations according to three measures-average time each customer is without power, time required to restore 90% of customers, and time required to restore 98% of customers. The optimization and simulation models both consider all the earthquakes that could affect the power system and represent the uncertainty surrounding expected restoration times. The models were developed through an application to the Los Angeles Department of Water and Power (LADWP) electric power system, but the general approach is extendable to other electric power systems, other lifelines, and other hazards. Copyright (C) 2006 John Wiley & Sons, Ltd.