| Title |
Robust global reverse logistics network redesign for high-grade plastic wastes recycling |
| ID_Doc |
16730 |
| Authors |
Xu, ZT; Elomri, A; Liu, WJ; Liu, H; Li, M |
| Title |
Robust global reverse logistics network redesign for high-grade plastic wastes recycling |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.wasman.2021.08.024 |
| Abstract |
The circular economy represents an alternative closed-loop production and consumption patterns instead of traditional linear take-make-waste approaches. It presents a new vision with global sustainability where plastic waste is viewed as a material that can be reused, to avoid depleting natural resources. In this context, it is essential to redesign the global reverse logistics network (GRLN) by incorporating the existing facilities across national boundaries into the integrated global recycling system. A mean-variance robust model with quadratic functions is developed to address the time-ambiguous currency exchange rate, the ocean freight rate, and the carbon prices. To the best of our knowledge, this is one of the first efforts to evaluate the effects of the multiplicative relationships between the uncertain elements, e.g. currency exchange rate and carbon trading prices. In the proposed model, the economic and the environmental performances of a GRLN are evaluated by the robustness coefficient. The application of the model is demonstrated in a sample case of the PWR between China and Belgium. The analysis shows that a lower robustness coefficient leads to a higher cost of the GRLN, but lower emissions. It is worthy to note that considering the maritime emission is not definite to guarantee global net sustainability. Moreover, a social GRLN network leads to a more cost-efficient system compared to developing two recycling networks individually in the importing and the exporting countries. |
| Author Keywords |
Reverse logistics; Circular economy; Robust optimization; Mean-variance; Carbon trading |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000692322300009 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
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