Abstract
Abstract The literature for capacity planning and scheduling of biopharmaceutical facilities has relied on mostly discrete-time mixed-integer linear programming (MILP) formulations. This work presents a new genetic algorithm (GA) based optimisation approach for medium-term capacity planning of a multi-product, multi-suite biopharmaceutical facility using a continuous-time representation. The continuous-time model is implemented by utilising a dynamic chromosome structure capable of adapting to the problem by growing in length from a single gene corresponding to a production campaign in a manufacturing schedule. The proposed optimisation approach is validated on a previously published industrial case study solved with a continuous-time MILP formulation. The results indicate that the proposed approach is both robust and fast at solving a medium-term scheduling problem from biopharmaceutical industry.
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