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The growth of the service sector of the United States economy has led to problems of scheduling personnel. In particular, as customer demand varies throughout the day the number of employees required also varies. Assigning personnel to shift types in order to match varying workload requirements is known as shift scheduling. The research reported here addresses the personnel shift scheduling problem using a computer-aided approach. A complete scheduling model is developed which generates employee requirements, schedules employees, provides an evaluation of the schedule, and allows system iteration to improve the schedule. This is accomplished by a computer package which combines queueing analysis, goal programming, and simulation. It is shown that the Computer-Aided Personnel Scheduling model (CAPS) provide valuable flexibility which is unavailable with models found in the literature. Objectives related to employee target levels both for each period and for the entire schedule. Cost factors are included to provide the decision maker a wide range of options for priority assignments to the objectives. This also includes the capability of developing a schedule with or without workforce size restrictions. Further flexibility is provided by the potential to consider one time period at a time. This proves to be a valuable asset in decreasing the total schedule cost. The structure of CAPS also allows for the recognition of objectives or cost factors which cannot be modelled in the mathematical framework. Thus, CAPS can be used to address a true but unmodelled objective. Performance of the scheduling model is demonstrated through a comparison with two widely known models, representing both heuristic and optimization approaches. The comparison is based upon example problems solved using each technique. These comparisons illustrate that a set of priorities can be established for CAPS which result in lower total schedule cost. Finally, the decision maker plays a key role in the CAPS methodology. This includes specifying inputs, stating scheduling objectives, evaluating schedule performance, and providing feedback for model iteration. Active participation by the decision maker should improve schedule performance and acceptability of CAPS as a scheduling procedure.