2. flexible assignment: An operation can be processed by one or more hardware modules in the laboratory, and the assignment of operations to hardware modules is a subproblem of the scheduling problem. Following the classification by Maravelias, the library synthesis scheduling problem falls into the category of flexible job-shop scheduling problem (FJSP) due to characteristics 1 and 2. The term "flexible" indicates that a specific operation may be processed by one of many machines. FJSP was first introduced by Brucker and Schlie in 1990 to model linear operation sequences in multipurpose facility environments, and is at least as hard as the NP-complete job-shop scheduling problem. FJSP has since been extended to include arbitrary inter-operation precedence relations, sometimes referred to as the extended FJSP, which maps to the dependent synthetic routes issue in library synthesis (characteristics 3). Previous studies have further generalized extended FJSP to include additional hard constraints. For example, Pawar and Bhosale investigated a FJSP in press working industry with the machine capacity constraints. Braune and Doerner focuses on scheduling workflows in chemical research laboratories with maximum time lag constraints. Boyer et al. introduced "generalized FJSP" to include machine setup time and holding time in addition to aforementioned hard constraints. While these previous studies include constraints that could partially map onto the constraints in library synthesis, none of these previous studies fully covers the types of constraints that are commonly seen in organic synthesis (Table ). We found the study by Boyer et al., despite being designed for ring rolling processes, most comprehensive in terms of constraint types, and their formulation is modified to accommodate library synthesis scheduling in this study (Section 2.2). In this study, we report an open-source library synthesis scheduler along with visualization modules (Figure ). Our formulation optimizes the makespan of arbitrary batch chemistry synthetic routes while respecting common laboratory-relevant constraints, including minimum/maximum lag time, hardware capacity, and work shifts. Our workflow produces optimal schedules for library synthesis by representing synthetic routes (proposed by predictive chemistry models) as reaction and operation networks. We demonstrate the scheduler on exemplary real-world chemical libraries, including a library for cannabinoid receptors and a library of FDA-approved drugs. ...