Pandora is an upcoming NASA SmallSat mission that will observe transiting exoplanets to study their atmospheres and the variability of their host stars. Efficient mission planning is critical for maximizing the science achieved with the year-long primary mission. To this end, we have developed a scheduler based on a metaheuristic algorithm that is focused on tackling the unique challenges of time-constrained observing missions, like Pandora. Our scheduling algorithm combines a minimum transit requirement metric, which ensures we meet observational requirements, with a “quality” metric that considers three factors to determine the scientific quality of each observation window around an exoplanet transit (defined as a visit). These three factors are: observing efficiency during a visit, the amount of the transit captured by the telescope during a visit, and how much of the transit captured is contaminated by a coincidental passing of the observatory through the South Atlantic Anomaly (SAA). The importance of each of these factors can be adjusted based on the needs or preferences of the science team. Utilizing this schedule optimizer, we develop and compare a few schedules with differing factor weights for the Pandora SmallSat mission, illustrating trade-offs that should be considered between the three quality factors. We also find that under all scenarios probed, Pandora will not only be able to achieve its observational requirements using the planets on the notional target list but will do so with significant time remaining for ancillary science.