We deal with the capacity planning problem of a biopharmaceutical firm or other firms with long and risky product development cycles. These firms need to balance the risk of delaying the start of production once the product is approved for market and the risk of unused capacity if the product development fails. If a clinical trial ends with the product being declined by the regulatory authorities no demand exists. In case of a successful trial, the demand level is uncertain as it is also for the existing drug portfolio. For the capacity investment decisions, two types of actions are available: Building a new plant or transferring the process to an existing plant in the network with idle capacity, which could also be a contract manufacturing organization. In biomanufacturing, transferring a production process to a new plant entails an uncertain effective yield in the new location. To determine the optimal capacity investment strategy under uncertainty, we formulate the problem as a stochastic programming model as well as a Markov Decision Process, comparing the solutions of both methodologies.
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We deal with the capacity planning problem of a biopharmaceutical firm or other firms with long and risky product development cycles. These firms need to balance the risk of delaying the start of production once the product is approved for market and the risk of unused capacity if the product development fails. If a clinical trial ends with the product being declined by the regulatory authorities no demand exists. In case of a successful trial, the demand level is uncertain as it is also for the...
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