Designing a sustainable fish closed-loop supply chain network under uncertainty

Area of Science:

• Operations Research
• Supply Chain Management
• Environmental Sustainability

Background:

• Growing importance of sustainable supply chain (SC) and reverse logistics (RL) in the food sector.
• Fish is a high-value, perishable food product with significant waste recycling potential.
• Need for integrated approaches to manage complex food supply chains.

Purpose of the Study:

• To investigate and optimize a sustainable closed-loop supply chain (CLSC) for fish.
• To develop a multi-objective mathematical model addressing uncertainty and sustainability criteria.
• To balance production rates, distribution, costs, social issues, and environmental impacts (CO2 emissions, waste).

Main Methods:

• Development of a multi-objective mathematical model under uncertainty.
• Application of exact, meta-heuristic, and hybrid meta-heuristic algorithms for optimization.
• Utilized Taguchi method, ANOVA, and the ε-constraint method for solution evaluation and validation.
• Case study of a trout CLSC in Northern Iran.

Main Results:

• The proposed model and algorithms demonstrate outstanding consistency and efficiency.
• Optimal solutions were found by balancing competing objectives including cost, social, and environmental factors.
• Sensitivity analyses confirmed the efficacy of the proposed algorithms and network design.

Conclusions:

• The study provides a robust framework for sustainable CLSC management in the fish industry.
• The integrated approach effectively addresses economic, social, and environmental dimensions.
• The findings highlight the practical applicability and efficiency of the developed methods for perishable food supply chains.