Traffic delays caused by pavement maintenance activities are a major concern to transportation engineers. There is a need to carefully plan and schedule such activities in order to minimize traffic delays. Unfortunately, this is a complex problem that cannot be easily solved by means of conventional optimization tools. A scheduling methodology is presented that uses genetic algorithms (GAs) to minimize traffic delays subject to constraints of maintenance operational requirements. The flexibility in problem modeling and the robust search capability of the GA technique make it a practical analytical tool for this problem. Pavement distress conditions, traffic flow data, and maintenance requirements are the major input parameters of the problem. Based on Singapore's maintenance practice and traffic delay models for four-lane two-way primary roads, a computer program has been developed. This program is applied to solve a hypothetical numerical example problem to illustrate the formulation and solution procedure of the proposed methodology.