1191. Optimizing the tailoring of the Dutch medicines stockpiling policy
Invited abstract in session TD-11: Pharmaceuticals and manufacturers, stream OR in Healthcare (ORAHS).
Tuesday, 14:30-16:00Room: Clarendon SR 1.03
Authors (first author is the speaker)
| 1. | Marie Baratto
|
| Technology and Operations management, Rotterdam School of Management, Erasmus University | |
| 2. | Harwin de Vries
|
| Rotterdam School of Management | |
| 3. | Thomas Breugem
|
| Humanitarian Research Group, INSEAD | |
| 4. | Stef Lemmens
|
| Technology and Operations Management, Rotterdam School of Management |
Abstract
Medicine shortages are a worldwide global challenge, prompting countries to develop mitigation strategies, including stockpiling. In the Netherlands, stockpile quantities are uniform across all medicines. This “one-size-fits-all” approach is ineffective, whereas tailored policies —specifying different minimum stock levels for different categories of medicines— can enhance supply resilience and reduce costs. However, tailoring increases policy complexity, which must be balanced with simplicity for ease of implementation and governance. Decision trees offer an elegant way to navigate this trade-off.
We develop a general approach for optimal stockpiling decision trees, ensuring simplicity and practicality, and apply it to the Dutch case.
Our research is in line with recent work on optimal descriptive, classification and prescriptive trees which apply machine learning and optimization techniques to solve mixed integer optimization formulations of decision tree problems. Unlike traditional greedy heuristics, we aim to construct the tree in a single step by solving an MILP formulation. To balance tailoring and simplicity, we explore various tree structures, such as symmetrical complete trees and incomplete trees. In collaboration with the Dutch government and pharmaceutical stakeholders, we apply our model to optimize stockpile levels, developing a cost-effective policy that is practical for implementation and strengthens pharmaceutical supply resilience.
Keywords
- Supply Chain Management
- Decision Theory
- Optimization Modeling
Status: accepted
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