multi-objective green supply chain network design considering carbon emissions and electricity consumption

This study aims to design a green closed-loop supply chain network (gclscn) for battery products, balancing economic efficiency, environmental responsibility, and timely customer delivery. the main objectives include minimizing total cost, energy consumption, and carbon emissions. a multi-objective mathematical model is developed, covering suppliers, production plants, distribution centers, customers, collection centers, recycling units, and disposal facilities with different capacities and technologies. to address the problem, two multi-objective metaheuristic algorithms, nsga-ii and nrga, are applied and compared based on solution diversity, closeness to the ideal solution, pareto set size, and computation time. demand uncertainty is included to better reflect real conditions. results show that nsga-ii provides a broader and more diverse set of solutions, offering decision-makers greater flexibility, while nrga delivers better computational efficiency. considering variable capacities and uncertain demand improves the model's practicality and robustness. overall, this research presents a comprehensive framework for sustainable closed-loop supply chain design in the battery industry and offers useful insights for practitioners, while supporting future studies involving dynamic modeling and advanced uncertainty techniques.