Abstract
In this paper, a multi-period multi-echelon reverse logistics network design problem under high extent of uncertainty is addressed. We first formulate and then solve the multi-period network design model using the cloudbased design optimization framework which ensures to: (1) handle high number of uncertain factors; (2) propose alternative solution to traditional approaches; (3) provide a robust solution which strengthens decision makers against unexpected situations. Finally, applicability of the presented approach is tested through a dataset of e-waste reverse logistics network.
Original language | English |
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Pages (from-to) | 1168-1185 |
Number of pages | 18 |
Journal | International Journal of Computational Intelligence Systems |
Volume | 10 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2017 |
Bibliographical note
Publisher Copyright:© 2017, the Authors.
Keywords
- Cloud based design optimization
- Mixed integer programming
- Network design
- Reverse logistics
- Uncertainty