A hierarchical solution approach for multi-site capacity planning under uncertainty in the pharmaceutical industry

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 work of Papageorgiou et al. (2001) determining both the product portfolio a...

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Bibliographic Details
Published in:Computers & chemical engineering 2004-05, Vol.28 (5), p.707-725
Main Authors: Levis, Aaron A., Papageorgiou, Lazaros G.
Format: Article
Language:English
Subjects:
Clinical trials uncertainty
Mixed integer optimisation
Multi-site capacity planning
Pharmaceutical industry
Trading structure
Two-stage programming
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Summary: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 work of Papageorgiou et al. (2001) determining both the product portfolio and the multi-site capacity planning in the face of uncertain clinical trials outcomes while taking into account the trading structure of the company. 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 solution approach is demonstrated by a number of illustrative examples.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2004.02.012