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Related Experiment Video

Updated: Oct 21, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Carbon-efficient closed-loop supply chain network: an integrated modeling approach under uncertainty.

Hamed Soleimani1,2, Mahsa Mohammadi3, Masih Fadaki4

  • 1School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia. hamed.soleimani@unimelb.edu.au.

Environmental Science and Pollution Research International
|September 4, 2021
PubMed
Summary

This study presents a robust optimization approach for designing green closed-loop supply chains. It balances cost and environmental sustainability under demand uncertainty, offering efficient solutions for circular economy business models.

Keywords:
Augmented Weighted Tchebycheff approachClosed-loop supply chainGreen supply chainMulti-objective optimizationRobust optimizationε-Constraint method

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Environmental Sustainability

Background:

  • Circular economy principles drive policies for recycling, remanufacturing, and reuse to enhance economic value while protecting the environment.
  • Designing sustainable business processes involves an inherent trade-off between environmental and economic factors.
  • Supply chain management faces increased complexity when demand uncertainty is introduced.

Purpose of the Study:

  • To investigate the design of a closed-loop supply chain (CLSC).
  • To evaluate competing objectives of cost minimization and environmental sustainability in CLSC operations under demand uncertainty.
  • To develop a comprehensive model integrating cost and carbon emission reduction.

Main Methods:

  • Employed Augmented Weighted Tchebycheff (AWT) and ε-constraint methods for multi-objective optimization.
  • Applied a robust optimization approach to manage demand uncertainty.
  • Integrated cost and sustainability objectives into a comprehensive CLSC design model.

Main Results:

  • The proposed approach effectively addresses the trade-offs between cost and environmental sustainability in CLSC design.
  • Efficient solutions were generated for designing green closed-loop supply chain networks.
  • Demonstrated the feasibility of balancing economic and environmental goals under uncertain demand.

Conclusions:

  • The study provides a robust framework for designing sustainable closed-loop supply chains.
  • The integrated model successfully handles multi-objective decision-making in the presence of demand uncertainty.
  • The findings support the adoption of circular economy principles in supply chain management for enhanced economic and environmental performance.