A multi-objective production planning problem with the consideration of time and cost in clinical trials

Hui Zhao, Edward Huang, Runliang Dou, Kan Wu*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

21 Scopus citations


Under increasingly challenging circumstances, pharmaceutical companies try to reduce the overproduction of clinical drugs, which is commonly seen in the pharmaceutical industry. When the overproduction is simply reduced without an efficient coordination of the inventories in the supply chain, the stock-outs at clinical sites and clinical trial delay can hardly be avoided. In this study, we propose a multi-objective model to optimize the production quantity, where the clinical trial duration and the total production and operational costs are minimized. The problem is formulated as a multi-stage stochastic programming model to capture the dynamic inventory allocation process in the supply chains. Since this problem's solving time and required memory can increase significantly with the increase of the stage and scenario numbers, the progressive hedging algorithm is applied as the solution approach in this paper. In the numerical experiments, we study this algorithm's performance and compare the solving efficiency with the direct solution approach. In addition, we identify the optimal production quantity of clinical drugs and give a discussion about the tradeoffs between the clinical trial delay and total cost.

Original languageEnglish
Pages (from-to)25-38
Number of pages14
JournalExpert Systems with Applications
StatePublished - 15 06 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd


  • Clinical trial
  • Multi-stage stochastic programming
  • Production and distribution planning
  • Progressive hedging algorithm
  • Supply chain management


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