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<p>Green inventory systems are critical for reducing carbon emissions and promoting sustainable supply chains, especially for perishable goods where deterioration and waste directly impact profitability and environmental performance. Existing models often overlook combined effects of price-sensitive demand, time-dependent deterioration, and carbon tax policies under uncertainty, limiting their practical applicability. This study aims to develop a sustainable inventory model for perishable items that optimizes both economic and environmental objectives. Using an EOQ framework with price-dependent demand and time-varying deterioration, the model incorporates a fuzzy approach with hexagonal fuzzy numbers to address uncertainties in cost parameters. A carbon tax policy is embedded to quantify environmental impact from transportation, storage, and spoilage. Results from numerical experiments show optimal cycle lengths, selling prices, and order quantities that enhance profit while reducing emissions. The model’s validity is demonstrated through sensitivity analysis, highlighting its adaptability to changes in key parameters and its potential as a decision-support tool for sustainable inventory management.</p>

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Sustainable Inventory Management for Perishable Goods: A Fuzzy EOQ Model with Carbon Tax Policy

  • 期刊论文

  • 发表日期：

    2025年12月9日

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  • Sahedev,
  • Vidhi Saini,
  • Anubhav Pratap Singh,
  • Yogendra Kumar Rajoria

摘要

Green inventory systems are critical for reducing carbon emissions and promoting sustainable supply chains, especially for perishable goods where deterioration and waste directly impact profitability and environmental performance. Existing models often overlook combined effects of price-sensitive demand, time-dependent deterioration, and carbon tax policies under uncertainty, limiting their practical applicability. This study aims to develop a sustainable inventory model for perishable items that optimizes both economic and environmental objectives. Using an EOQ framework with price-dependent demand and time-varying deterioration, the model incorporates a fuzzy approach with hexagonal fuzzy numbers to address uncertainties in cost parameters. A carbon tax policy is embedded to quantify environmental impact from transportation, storage, and spoilage. Results from numerical experiments show optimal cycle lengths, selling prices, and order quantities that enhance profit while reducing emissions. The model’s validity is demonstrated through sensitivity analysis, highlighting its adaptability to changes in key parameters and its potential as a decision-support tool for sustainable inventory management.