In this study, the problem of scheduling chemical library synthesis is formalized as a generalized FJSP. A MILP formulation is proposed to consider common laboratory constraints including lag time, module capacity, and work shifts. Two scheduling algorithms, a greedy heuristic (baseline scheduler) and a MILP formulation, are evaluated for their ability to minimize the total makespan (duration) of a library synthesis campaign. To test the proposed schedulers, 720 scheduling instances are built from hypothetical synthetic routes to realistically accessible chemical libraries involving 3 to 63 reaction steps, or 20 to 402 operations. Within the 3-hour wall time limit, the MILP scheduler is able to produce optimal and suboptimal schedules for 363 and 323 scheduling instances, respectively, leaving 34 instances for which no feasible solution can be found. Compared to the baseline schedules, the optimal MILP schedules show makespan reductions ranging from 0% (very small libraries) to 58% (large libraries) with an average of 20%. We find that the baseline schedule can approximate optimal operation-to-module assignments but fails to approximate optimal operation sequences. Two illustrative case studies show that optimal schedules greatly reduce makespan and improve module utilization for synthesis campaigns of both linear routes and tree routes compared to baseline schedules.