Enhancing Circularity in Medical Device Supply Chains by Optimizing EoL Decisions Through Reinforcement Learning: A Multi-Objective Approach

Soufiane El Bechari, Oualid Jouini, Zied Jemai, Zied Jemai, Fourat Trabelsi, Robert Heidsieck

2025

Abstract

Circular supply chains are becoming essential in the pursuit of sustainability, as they promote the responsible disposal, recycling, and reuse of products at the end of their life cycles. This research, developed in collaboration with GE HealthCare, presents a multi-objective optimization framework that incorporates environmental, economic, and circularity performance in end-of-life (EoL) decision-making. The proposed model leverages historical data on reuse and recycling success rates to capture the operational realities of circular supply chains. By employing Q-learning, this paper aims to develop a decision-support mechanism that optimizes EoL actions for components, thereby enhancing the circularity, reducing carbon footprint, and minimizing economic costs within the circular supply chain.

Paper Citation

in Harvard Style

El Bechari S., Jouini O., Jemai Z., Trabelsi F. and Heidsieck R. (2025). Enhancing Circularity in Medical Device Supply Chains by Optimizing EoL Decisions Through Reinforcement Learning: A Multi-Objective Approach. In Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES; ISBN 978-989-758-732-0, SciTePress, pages 88-99. DOI: 10.5220/0013122400003893

in Bibtex Style

@conference{icores25,
author={Soufiane El Bechari and Oualid Jouini and Zied Jemai and Fourat Trabelsi and Robert Heidsieck},
title={Enhancing Circularity in Medical Device Supply Chains by Optimizing EoL Decisions Through Reinforcement Learning: A Multi-Objective Approach},
booktitle={Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES},
year={2025},
pages={88-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013122400003893},
isbn={978-989-758-732-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES
TI - Enhancing Circularity in Medical Device Supply Chains by Optimizing EoL Decisions Through Reinforcement Learning: A Multi-Objective Approach
SN - 978-989-758-732-0
AU - El Bechari S.
AU - Jouini O.
AU - Jemai Z.
AU - Trabelsi F.
AU - Heidsieck R.
PY - 2025
SP - 88
EP - 99
DO - 10.5220/0013122400003893
PB - SciTePress