Medium term planning of biopharmaceutical manufacture under uncertainty

Manufacturers in the biopharmaceutical industry face greater scheduling and planning challenges as the trend of employing multiproduct manufacturing facilities continues to grow. These challenges are complicated by the randomness inherent in the biopharmaceutical manufacturing environment. This work focuses on capturing the effect of uncertainties in fermentation titres when optimising planning of biopharmaceutical manufacturing campaignsIn this paper we extend our previous deterministic medium term planning formulation to include uncertain production rates resulting in a two stage, multi-scenario, mixed-integer linear programming (MILP) model. When tested on industrial-sized problems, the resulting MILP problem proved intractable. An iterative solution algorithm is proposed for solving the resulting large scale MILP planning problem. The applicability of the algorithm is demonstrated through three illustrative examples.The computational results indicate that the proposed solution algorithm offers a significant reduction in the computational requirements whilst maintaining solution quality. The proposed optimisation-based framework presents an opportunity for biomanufacturers to make better medium term planning decisions, particularly under uncertain manufacturing conditions.