Modelling and solving sustainable supply chain network design based on graph autoencoder clustering algorithm
| Year of publication: |
2025
|
|---|---|
| Authors: | Guo, Yuhan ; Chen, Runsheng ; Boulaksil, Youssef ; Allaoui, Hamid |
| Published in: |
International journal of production research. - London [u.a.] : Taylor & Francis, ISSN 1366-588X, ZDB-ID 1485085-0. - Vol. 63.2025, 24, p. 10000-10026
|
| Subject: | clustering | graph autoencoder | solution mapping mechanism | supply chain design | Sustainability | Lieferkette | Supply chain | Graphentheorie | Graph theory | Algorithmus | Algorithm | Regionales Cluster | Regional cluster | Nachhaltigkeit | Unternehmensnetzwerk | Business network | Clusteranalyse | Cluster analysis | Nachhaltige Entwicklung | Sustainable development | Mathematische Optimierung | Mathematical programming |
-
Local search for constrained graph clustering in biological networks
Tran, Duy Hoang, (2021)
-
Wang, Yuexia, (2025)
-
Cluster-based supplier segmentation : a sustainable data-driven approach
Rahiminia, Mohammad, (2023)
- More ...
-
Modelling and analysis of online ride-sharing platforms : a sustainability perspective
Guo, Yuhan, (2023)
-
A distributed approximation approach for solving the sustainable supply chain network design problem
Guo, Yuhan, (2019)
-
A prediction-based iterative Kuhn-Munkres approach for service vehicle reallocation in ride-hailing
Guo, Yuhan, (2024)
- More ...