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<p>This study develops an integrated framework that aligns supply chain networks with sustainable practices under the advanced technological landscape of Industry 5.0. The model incorporates Industry 5.0 development factors, sustainability objectives, and circular closed-loop supply chain principles, targeting cost reduction, enhanced technology utilization, improved sustainability performance, and optimized closed-loop processes. A hybrid Multi-Objective Evolutionary Algorithm (MOEA) combining NSGA-IV, SMS-EMOA, and ε-MOEA is developed to solve this complex optimization problem. Comprehensive validation using 28 real-world industrial cases (2019–2023) demonstrates the algorithm’s effectiveness, achieving cost reductions of 15% in small-scale, 12% in medium-scale, and 10% in large-scale implementations. Additionally, the algorithm assesses Generational Distance (GD), Hypervolume (HV), Error Ratio (ER), and Overall Non-Dominated Vector Generation (ONVG) in this context. The results reveal significant improvements including 22% better GD indicating enhanced convergence, 19% greater HV coverage reflecting improved diversity, 31% lower ER demonstrating higher accuracy, and 27% higher ONVG confirming superior solution spread. The framework maintains robust performance with solution quality stability within 8% under operational variations including ±20% budget fluctuations and ± 10% mutation rate ranges. These findings provide both theoretical advancements in multi-objective optimization and practical decision-support tools for implementing sustainable Industry 5.0 supply chains, demonstrating effective balance between economic, technological and environmental objectives in complex operational environments.</p>

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Synergizing industry 5.0 development factors into sustainable circular closed-loop supply chains through a hybrid approach: Case studies

  • 期刊论文

  • 发表日期：

    2025年10月13日

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  • Farnaz Javadi Gargari,
  • Zahra Saeidi-Mobarakeh,
  • Hossein amoozad khalili

摘要

This study develops an integrated framework that aligns supply chain networks with sustainable practices under the advanced technological landscape of Industry 5.0. The model incorporates Industry 5.0 development factors, sustainability objectives, and circular closed-loop supply chain principles, targeting cost reduction, enhanced technology utilization, improved sustainability performance, and optimized closed-loop processes. A hybrid Multi-Objective Evolutionary Algorithm (MOEA) combining NSGA-IV, SMS-EMOA, and ε-MOEA is developed to solve this complex optimization problem. Comprehensive validation using 28 real-world industrial cases (2019–2023) demonstrates the algorithm’s effectiveness, achieving cost reductions of 15% in small-scale, 12% in medium-scale, and 10% in large-scale implementations. Additionally, the algorithm assesses Generational Distance (GD), Hypervolume (HV), Error Ratio (ER), and Overall Non-Dominated Vector Generation (ONVG) in this context. The results reveal significant improvements including 22% better GD indicating enhanced convergence, 19% greater HV coverage reflecting improved diversity, 31% lower ER demonstrating higher accuracy, and 27% higher ONVG confirming superior solution spread. The framework maintains robust performance with solution quality stability within 8% under operational variations including ±20% budget fluctuations and ± 10% mutation rate ranges. These findings provide both theoretical advancements in multi-objective optimization and practical decision-support tools for implementing sustainable Industry 5.0 supply chains, demonstrating effective balance between economic, technological and environmental objectives in complex operational environments.