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<p>The increasing demand for sustainable supply chains has made supplier selection and distribution process increasingly complex, especially in resource-intensive industries like steel. This study addresses the challenge by proposing a decision-making framework integrating sustainable supplier selection, order allocation and product distribution under an uncertain environment. Different criteria of supplier selection process are prioritized and weighted using BWM method in the first phase. An integrated model with six objective functions, incorporating the generated weights, is then developed to create allocation and distribution patterns. To improve robustness of the model, transportation costs are considered in the form of fuzzy triangular numbers. Tested on an Indian steel firm, the model allocated up to 650 units to the best performing suppliers and efficiently routed 1800 units maintaining an approximate satisfaction rate of 85% in key objectives. Different scenarios are created based on varying weights of different objectives. Moreover, the model is also extended for stochastic uncertainty in the parameters handling the vague information existing in real-life problems. The framework offers a potential and practical tool for sustainable supply chain planning under uncertainty.</p>

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Decision-Making Framework for Sustainable Supplier Evaluation and Product Distribution under Uncertainty: A Steel Industry Case

  • 期刊论文

  • 发表日期：

    2025年8月22日

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  • Syed Mohd Muneeb,
  • Zainab Asim,
  • Mitra Amini,
  • Syed Aqib Jalil

摘要

The increasing demand for sustainable supply chains has made supplier selection and distribution process increasingly complex, especially in resource-intensive industries like steel. This study addresses the challenge by proposing a decision-making framework integrating sustainable supplier selection, order allocation and product distribution under an uncertain environment. Different criteria of supplier selection process are prioritized and weighted using BWM method in the first phase. An integrated model with six objective functions, incorporating the generated weights, is then developed to create allocation and distribution patterns. To improve robustness of the model, transportation costs are considered in the form of fuzzy triangular numbers. Tested on an Indian steel firm, the model allocated up to 650 units to the best performing suppliers and efficiently routed 1800 units maintaining an approximate satisfaction rate of 85% in key objectives. Different scenarios are created based on varying weights of different objectives. Moreover, the model is also extended for stochastic uncertainty in the parameters handling the vague information existing in real-life problems. The framework offers a potential and practical tool for sustainable supply chain planning under uncertainty.