The purpose of this study is to develop a comprehensive approach for green supplier selection that integrates traditional and green criteria, facilitating the creation of an optimal procurement policy aligned with sustainable development goals.
This study uses a multi-objective model for green supplier selection, incorporating the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) for supplier ranking. Eight objective functions and seven constraints are considered in the formulation of the model. In addition, a genetic algorithm (GA), a metaheuristic approach, is applied to enhance the efficiency of the supplier selection process.
The outcomes of the study provide valuable insights for managers, enabling them to make informed decisions regarding supplier selection. The model facilitates the identification of suppliers that not only meet traditional criteria but also align with green considerations, thereby optimizing the overall supply chain efficiency.
Despite its strengths, this study has several limitations. The model’s effectiveness may vary depending on the specific context and industry dynamics. In addition, the availability and accuracy of data could influence the outcomes of the supplier selection process.
The findings of this study have significant practical implications for businesses aiming to adopt sustainable practices in their supply chain operations. By implementing the proposed model, managers can streamline their supplier selection process and ensure that their procurement policies are in line with both traditional and green criteria.
This study contributes to the existing literature by offering a comprehensive approach to green supplier selection that integrates traditional and green criteria. The incorporation of TOPSIS and GAs enhances the efficiency and effectiveness of the supplier selection process, providing a novel framework for sustainable procurement practices.
