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<p>In light of increasing environmental challenges, integrating sustainability into supply chain management has become vital for achieving global environmental objectives. This study focuses on developing a low-carbon supply chain inventory model specifically designed for deteriorating items under inflationary conditions. It highlights the importance of preservation technologies and green investments as strategies for reducing carbon emissions while maintaining profitability. Using a fuzzy learning approach, the research explores the continuous inventory model that aim to balance economic efficiency with environmental responsibility. The model accounts for the dependency of demand on both selling price and carbon emission reductions, providing algorithms to determine optimal solutions in both crisp and fuzzy environments. Key decision variables, including optimal selling price, production cycle length, and preservation investments, are analyzed to maximize total profit. Numerical results validate the effectiveness of the proposed approach. The total system profit (STP) increases by 18.96% in the fuzzy case compared to the crisp case, demonstrating the benefits of incorporating uncertainty. Furthermore, the fuzzy learning approach leads to an even higher improvement, with 19.72% greater profit than the crisp model. These findings highlight that the fuzzy learning model effectively manages uncertainty and enhances financial performance compared to conventional approaches. Additionally, sensitivity analysis offers practical insights into how inflation, demand shifts, and preservation costs influence system performance. These findings make the model particularly relevant for practitioners and policymakers seeking to design efficient and sustainable supply chains that are both economically viable and environmentally friendly. By bridging the gap between sustainability and profitability, this research contributes to the development of robust inventory management strategies in low-carbon supply chains, addressing critical issues related to deteriorating products, inflation, and green investments.</p>

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Optimizing Sustainability: A Fuzzy Learning Approach to Low Carbon Supply Chain for Deteriorating Items with Preservation and Green Investment under Inflationary Environment

  • 期刊论文

  • 发表日期：

    2025年9月30日

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  • Vaishali Singh,
  • Ummeferwa Zaiddi,
  • S. R. Singh,
  • Neha Saxena

摘要

In light of increasing environmental challenges, integrating sustainability into supply chain management has become vital for achieving global environmental objectives. This study focuses on developing a low-carbon supply chain inventory model specifically designed for deteriorating items under inflationary conditions. It highlights the importance of preservation technologies and green investments as strategies for reducing carbon emissions while maintaining profitability. Using a fuzzy learning approach, the research explores the continuous inventory model that aim to balance economic efficiency with environmental responsibility. The model accounts for the dependency of demand on both selling price and carbon emission reductions, providing algorithms to determine optimal solutions in both crisp and fuzzy environments. Key decision variables, including optimal selling price, production cycle length, and preservation investments, are analyzed to maximize total profit. Numerical results validate the effectiveness of the proposed approach. The total system profit (STP) increases by 18.96% in the fuzzy case compared to the crisp case, demonstrating the benefits of incorporating uncertainty. Furthermore, the fuzzy learning approach leads to an even higher improvement, with 19.72% greater profit than the crisp model. These findings highlight that the fuzzy learning model effectively manages uncertainty and enhances financial performance compared to conventional approaches. Additionally, sensitivity analysis offers practical insights into how inflation, demand shifts, and preservation costs influence system performance. These findings make the model particularly relevant for practitioners and policymakers seeking to design efficient and sustainable supply chains that are both economically viable and environmentally friendly. By bridging the gap between sustainability and profitability, this research contributes to the development of robust inventory management strategies in low-carbon supply chains, addressing critical issues related to deteriorating products, inflation, and green investments.