The MILP scheduler may terminate before finding an optimal solution due to the applied time limit (Section 2.5), especially for the larger libraries that tend to be more complex MILP problems. Premature termination can result in either a set of feasible solutions (suboptimal schedules) or no feasible solution. The runtime trend is shown in Figure : While optimal schedules can be reliably found for small libraries (number of target chemicals ≤ 4), mid-size libraries (5 ≤ number of target chemicals ≤ 7) may result in only suboptimal schedules, and for large libraries (8 ≤ number of target chemicals), finding even feasible solutions becomes difficult. This is particularly true for scheduling instances including work shift constraints where more variables are needed. This also explains the fewer optimal schedules found for VS libraries compared to FDA libraries, as the former often includes more reactions/operations than the latter (Table ). Out of the 720 scheduling instances, optimal/suboptimal schedules are found for 363/323 of them, and for 34 of them no feasible solutions are found before reaching the time limit of 3 hours. As shown in Figure , temporal cost to find an optimal schedule increases exponentially with respect to the number of target chemicals. This suggest that time complexity is a limitation of the current MILP formulation, thus the motivation to explore better formulations or heuristic methods in future studies.