Stochastic optimization: pharmaceutical portfolios decision-making under uncertainty
Typ
Examensarbete för masterexamen
Program
Publicerad
2019
Författare
Carlsson, Nils
Sergejev, Dmitri
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The process of developing pharmaceutical drugs is long and costly, with a low
probability of an approved drug in the final stage. Given a portfolio of several
different pharmaceutical projects, it is therefore highly important to select the ones
that maximize the expected profit. This paper presents a mathematical optimization
model given the rules of a pharmaceutical project. The model is initially fully
deterministic but is later expanded to include stochastic constraints. A recourse view
of the problem is also discussed, meaning optimization under the assumption that
choices can be made based on the realization of stochastic variables. The deterministic
model is linear and thus straightforward to solve, while the stochastic constraints
introduce non-linearities that greatly increase the complexity of the problem. Possible
approaches to reduce this complexity are discussed, such as approximations and
linearizations, along with the best use of the models. The deterministic model is
also applied to a test portfolio and the results, such as the revenue, cost, solution
time and others are discussed in the light of combinatorial complexities and decisions
under risk.