Travel decision making is increasingly regarded as a highly complex process in which individuals not only decide about frequency of trips, travel modes, and routes, but also about activity participation and sequencing and timing and duration of activities and trips. This raises the question of whether or not traditional discrete-choice models still provide the best starting point for realistically modeling such a process. Some scholars consider computational process models (CPMs) a promising approach because they allow for heuristic search and suboptimal reasoning processes, which are typical for complex decision making. A model of activity scheduling, SMASH (Simulation Model of Activity Scheduling Heuristics), which incorporates aspects of discrete-choice modeling and CPMs, has been proposed. The model describes the pretrip planning phase, in which individuals decide which activities to perform, at what locations, at what times, in which sequence, and how to travel to the various activity sites. The calibration of this model, using data collected with the interactive computerized procedure MAGIC, has been described in the literature. The results indicated that when scheduling their activities, subjects seem to trade off attributes of activities (time constraints, duration), attributes of the schedule (time spent on activities, overall travel time, realism) and characteristics of the scheduling process (amount of effort already involved in the scheduling process) to obtain feasible schedules. More extensive tests, using simulation experiments, of the model's internal, predictive, and face validity are described. SMASH was used to predict subjects' activity schedules based on their activity agenda and information about their spatio-temporal circumstances. The predicted schedules were then compared with the activity schedules conceived by the subjects themselves under different circumstances, to assess the model's validity. The tests indicated that the model provided satisfactory results with respect to the reproduction of the observed activity schedules. The results of the validity test warrant the use of the model for assessing the effects of various policy measures such as time policies, land use policies, and travel demand management.