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<p>The Pharmaceutical Supply Chain (PSC) plays a critical role in healthcare systems while also generating significant environmental burdens due to pharmaceutical waste. Motivated by the growing emphasis on circular economy practices, this study proposes a novel multi-objective mathematical model for designing a circular pharmaceutical supply chain network integrating Industry 5.0 principles and IoT-enabled monitoring technologies. The proposed framework incorporates regulated reverse logistics and take-back systems to improve the safe collection, treatment, and recovery of end-of-life pharmaceutical products. In addition, the model accounts for sustainability objectives through CO₂ emission reduction, human-centricity through workforce fatigue constraints, and resilience enhancement via improved visibility and structural adaptability. The resulting optimization problem is solved using the Goal Attainment (GA) and Augmented Epsilon Constraint (AEC) methods. Sensitivity analyses are conducted to evaluate the impact of key parameters and provide managerial insights. The findings demonstrate that digital monitoring and circular reverse logistics can significantly improve sustainability and visibility while supporting a more resilient and human-centered PSC.</p>

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A Circular Pharmaceutical Supply Chain Network Integrating Industry 5.0 and IoT-Based Reverse Logistics

  • 期刊论文

  • 发表日期：

    2026年4月11日

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  • Zeinab Sazvar,
  • Shabnam Rekabi

摘要

The Pharmaceutical Supply Chain (PSC) plays a critical role in healthcare systems while also generating significant environmental burdens due to pharmaceutical waste. Motivated by the growing emphasis on circular economy practices, this study proposes a novel multi-objective mathematical model for designing a circular pharmaceutical supply chain network integrating Industry 5.0 principles and IoT-enabled monitoring technologies. The proposed framework incorporates regulated reverse logistics and take-back systems to improve the safe collection, treatment, and recovery of end-of-life pharmaceutical products. In addition, the model accounts for sustainability objectives through CO₂ emission reduction, human-centricity through workforce fatigue constraints, and resilience enhancement via improved visibility and structural adaptability. The resulting optimization problem is solved using the Goal Attainment (GA) and Augmented Epsilon Constraint (AEC) methods. Sensitivity analyses are conducted to evaluate the impact of key parameters and provide managerial insights. The findings demonstrate that digital monitoring and circular reverse logistics can significantly improve sustainability and visibility while supporting a more resilient and human-centered PSC.