Robust global reverse logistics network redesign for high-grade plastic wastes recycling.

Area of Science:

• Operations Research
• Environmental Science
• Supply Chain Management

Background:

• The traditional linear economy (take-make-waste) is unsustainable, necessitating a shift towards a circular economy.
• Plastic waste requires innovative solutions, viewing it as a reusable resource to conserve natural capital.
• Redesigning global reverse logistics networks (GRLN) is crucial for integrating international recycling efforts.

Purpose of the Study:

• To develop a robust model for optimizing GRLN considering economic and environmental factors.
• To evaluate the impact of uncertain variables like exchange rates, freight rates, and carbon prices.
• To analyze the multiplicative relationships between these uncertain elements in a GRLN.

Main Methods:

• A mean-variance robust model with quadratic functions was developed.
• The model incorporates time-ambiguous currency exchange rates, ocean freight rates, and carbon prices.
• Economic and environmental performances were assessed using a robustness coefficient, demonstrated with a China-Belgium case study.

Main Results:

• A lower robustness coefficient correlates with higher GRLN costs but reduced emissions.
• Maritime emissions alone do not guarantee overall global net sustainability.
• Integrated social GRLN are more cost-effective than separate national recycling networks.

Conclusions:

• The proposed model offers a robust approach to GRLN design for circular economy principles.
• Balancing economic and environmental goals in GRLN is complex due to interdependent uncertain factors.
• Global collaboration in reverse logistics is essential for achieving sustainable plastic waste management.