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A novel multi-objective robust possibilistic flexible programming to design a sustainable apparel closed-loop supply
Samira Rouhani1, Saman Hassanzadeh Amin1, Leslie Wardley2
1Department of Mechanical, Industrial and Mechatronics Engineering, Toronto Metropolitan University, Ontario, Canada.
Designing a sustainable apparel supply chain is crucial. This study introduces a novel optimization model that minimizes costs and environmental harm while maximizing social benefits, using hexagonal fuzzy numbers to handle uncertainties in returns.
Area of Science:
- Operations Research
- Supply Chain Management
- Environmental Science
Background:
- The apparel industry faces significant economic, environmental, and social challenges due to its linear supply chain model.
- Developing a sustainable Closed-Loop Supply Chain (CLSC) is essential to mitigate these adverse impacts.
- Existing CLSC models often struggle to address the complexities of diverse return types and uncertain quantities.
Purpose of the Study:
- To develop a novel tri-objective optimization model for designing a sustainable apparel CLSC network.
- To simultaneously minimize costs and environmental impacts while maximizing social benefits under uncertain demand and return conditions.
- To incorporate unique apparel industry facilities and optimize production environmental performance levels.
Main Methods:
- A hybrid robust possibilistic flexible programming model is developed, extending previous methodologies.
- The model uniquely utilizes hexagonal fuzzy numbers to represent uncertain epistemic parameters.
- The AUGMECON method with lexicographic optimization is employed to manage the multi-objective nature of the problem.
Main Results:
- The proposed model demonstrates superiority over methods using triangular fuzzy numbers, validated through comparative analysis.
- Commercial and End Of Use (EOU) returns were found to have a more significant negative impact on sustainability than End Of Life (EOL) returns.
- The model successfully optimizes environmental performance and considers flexible demand fulfillment constraints.
Conclusions:
- The developed model offers a robust framework for designing sustainable apparel CLSCs, effectively handling uncertainties and multiple objectives.
- Hexagonal fuzzy numbers provide a more advanced approach for modeling uncertainty in CLSC parameters compared to triangular fuzzy numbers.
- Addressing commercial and EOU returns is critical for enhancing the overall economic, environmental, and social sustainability of apparel CLSCs.
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