A growing biopharmaceutical industry with increasingly strong competitors forces its players to use their plants in the most efficient way and plan accurately to avoid high inventory costs or late delivery costs. This bachelor thesis contributes to the discussion about optimizing biopharmaceutical production in a medium-term planning. It provides a mixed integer linear program (MILP) to answer two key questions within the production process. Compared to other papers it uses a continuous time representation to increase utilization of the facility. It also includes uncertainties of titer formation and yield of resin to better reflect the reality; for this chance constrained programming (CCP) is applied. In order to evaluate the major changes of the proposed model in comparison to existing literature, modified variants of that model will be tested with a Monte Carlo simulation. As a result, the proposed model stands out for its accurate planning and a high profit.     «

A growing biopharmaceutical industry with increasingly strong competitors forces its players to use their plants in the most efficient way and plan accurately to avoid high inventory costs or late delivery costs. This bachelor thesis contributes to the discussion about optimizing biopharmaceutical production in a medium-term planning. It provides a mixed integer linear program (MILP) to answer two key questions within the production process. Compared to other papers it uses a continuous time rep...     »