Production Planning for Pharmaceutical Companies Under Non-Compliance Risk
Marco Laumanns (),
Eleni Pratsini (),
Steven Prestwich () and
Catalin-Stefan Tiseanu ()
Additional contact information
Marco Laumanns: IBM Research – Zurich
Eleni Pratsini: IBM Research – Zurich
Steven Prestwich: University College
Catalin-Stefan Tiseanu: University of Bucharest
A chapter in Operations Research Proceedings 2010, 2011, pp 545-550 from Springer
Abstract:
Abstract This paper addresses a production planning setting for pharmaceutical companies under the risk of failing quality inspections that are undertaken by the regulatory authorities to ensure good manufacturing practices. A staged decision model is proposed where the regulatory authority is considered an adversary with limited inspection budget, and the chosen inspections themselves have uncertain outcomes. Compact formulations for the expected revenue and the worst-case revenue as risk measures are given as well as a proof that the simplest version of the production planning problem under uncertainty is NP-complete. Some computational results are given to demonstrate the performance of the different formulations.
Keywords: Pharmaceutical Company; Risk Measure; Total Revenue; Good Manufacturing Practice; Uncertain Outcome (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-642-20009-0_86
Ordering information: This item can be ordered from
http://www.springer.com/9783642200090
DOI: 10.1007/978-3-642-20009-0_86
Access Statistics for this chapter
More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().