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 |
|---|---|
| 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.
Funding
This research has been conducted in partial support of the Istanbul Technical University Scientific Research Projects (ITU-BAP) Grant #38319. The authors are thankful to ITU-BAP for this support.
| Funders | Funder number |
|---|---|
| Istanbul Teknik Üniversitesi | |
| Bilimsel Araştırma Projeleri Birimi, İstanbul Teknik Üniversitesi | #38319 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Cloud based design optimization
- Mixed integer programming
- Network design
- Reverse logistics
- Uncertainty
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