Abstract
Abstract This paper presents a systematic mathematical programming approach for long-term, multi-site capacity planning under uncertainty in the pharmaceutical industry. The proposed mathematical model constitutes an extension of the previous work done by Papageorgiou et al. (2001) determining both the product portfolio and the multi-site capacity planning in the face of uncertain clinical trials outcomes. Two distinct decision-making levels are identified, namely the strategic level (here-and-now decisions) and the operational level (wait-and-see decisions) The overall problem is formulated as a two-stage, multi-scenario, mixed-integer linear programming (MILP) model. A hierarchical algorithm is then proposed in order to reduce the computational effort needed for the solution of the resulting large-scale MILP problem. The applicability of the proposed methodology is demonstrated by two illustrative examples.
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