Multi-Objective Pharmaceutical Portfolio Optimization under Uncertainty of Cost and Return
Mahboubeh Farid,
Hampus Hallman,
Mikael Palmblad and
Johannes Vänngård
Additional contact information
Mahboubeh Farid: Captario AB, 411 38 Gothenburg, Sweden
Hampus Hallman: Captario AB, 411 38 Gothenburg, Sweden
Mikael Palmblad: Captario AB, 411 38 Gothenburg, Sweden
Johannes Vänngård: Captario AB, 411 38 Gothenburg, Sweden
Mathematics, 2021, vol. 9, issue 18, 1-11
Abstract:
This paper presents the study of multi-objective optimization of a pharmaceutical portfolio when both cost and return values are uncertain. Decision makers in the pharmaceutical industry encounter several challenges in deciding the optimal selection of drug projects for their portfolio since they have to consider several key aspects such as a long product-development process split into multiple phases, high cost and low probability of success. Additionally, the optimization often involves more than a single objective (goal) with a non-deterministic nature. The aim of the study is to develop a stochastic multi-objective approach in the frame of chance-constrained goal programming. The application of the results of this study allows pharmaceutical decision makers to handle two goals simultaneously, where one objective is to achieve a target return and another is to keep the cost within a finite annual budget. Finally, the numerical results for portfolio optimization are presented and discussed.
Keywords: portfolio optimization; multi-objective; uncertainty; pharmaceutical industry (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7390/9/18/2339/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/18/2339/ (text/html)
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:gam:jmathe:v:9:y:2021:i:18:p:2339-:d:639703
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().