Abstract Most contributions on short-term scheduling of batch processes just account for limited availability of unary renewable resources like equipment items or individual workers Since they feature a capacity equal to one, two processing tasks requiring a common unary resource must be sequentially accomplished. However, production tasks also require another class of renewable resources like utilities (steam, electricity, cooling water) or labor pool, usually named finite resources. Since a finite resource has a capacity strictly greater than one, it can be shared by two or several processing tasks at any time as long as the overall resource requirement does not exceed the total available capacity. This work presents an efficient MILP continuous-time approach to multistage batch process scheduling subject to limited availability of unary and finite renewable resources. Continuous and discrete finite resources can both be considered. The approach is based on a rigorous continuous-time representation that handles a common set of sequencing variables for all finite resources. A large case study involving the scheduling of a multistage batch plant under unary and finite resource constraints have been solved at low CPU time.
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