In examples of automated chemistry platforms, an operation scheduler is typically reported as a component of the overall platform manager rather than as a standalone, reusable module. Most of these schedulers use rule-based, heuristic approximation methods. 11,15 For example, Canty uses a greedy algorithm to arrange concurrent workflows on a molecular synthesis platform. Simple prioritization policies are also popular choices for dynamic scheduling. The platform by Burger et al. uses an oldest-job-first policy, and the laboratory automation manager by Delaney et al. adopts a shortest-job-first policy. These simple scheduling policies, however, may not provide feasible solutions to comply with constraints that are common to chemical synthesis. A key constraint type is time lag constraints that restrict the temporal gap between the end of an operation and the start of another. For example, if a stock solution of a homogeneous catalyst is prone to deactivation by oxidation, there is a maximum time lag between the preparation of this solution and its addition to the reactor. A shortest-job-first or an oldest-job-first policy does not guarantee that the shortest/oldest next operation would obey such a maximum time lag constraint. Aarts et al.