一个分析驱动的循环供应链框架,集成了质量、保证和人力效率

Lalji Kumar, Uttam Kumar Khedlekar
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引用次数: 0

摘要

本文提出了一个先进的以人为中心的循环供应链优化框架,将经济、环境和行为维度整合到一个统一的多目标模型中。通过共同优化销售价格、产品质量、保修期和生产周期,该模型捕获了盈利能力和可持续性相关惩罚之间的复杂权衡。该框架的一个显著特点是结合了人类效率指数和基于循环的回报函数,从而能够对技能驱动的废物最小化和对质量敏感的消费者行为进行动态建模。由此产生的非线性优化问题使用四种强大的元启发式算法-基于教学的优化(TLBO),具有学习率的TLBO,非支配排序遗传算法II (NSGA-II)和多目标粒子群优化(MOPSO)来解决。大量的数值模拟证明了基于tlbo的方法在实现高利润、低惩罚解决方案方面的有效性,而统计分析通过Friedman检验和Wilcoxon符号秩检验证实了它们的稳健性和优越性。从管理的角度来看,该模型通过展示人类效率和产品生命周期属性对供应链绩效的非线性影响,为将运营决策与面向可持续发展的目标相一致提供了关键的见解。从政策的角度来看,研究结果主张建立制度性机制,激励对技能开发、循环利用和循环驱动设计实践的投资。此外,这项工作的社会意义在于它对工业5.0范式的贡献,在工业5.0范式中,包容性、可持续性和以人为本的生产系统被优先考虑。因此,这项研究为决策者提供了一个强大的、可操作的框架,帮助他们设计有弹性的、循环的供应链,促进长期经济价值和社会福利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An analytics-driven circular supply chain framework integrating quality, warranty, and human efficiency
This paper presents an advanced human-centric circular supply chain optimization framework that integrates economic, environmental, and behavioral dimensions into a unified multi-objective model. By jointly optimizing selling price, product quality, warranty duration, and production cycle time, the model captures the intricate trade-offs between profitability and sustainability-related penalties. A distinctive feature of the framework is the incorporation of a Human Efficiency Index and a circularity-based return function, enabling dynamic modeling of skill-driven waste minimization and quality-sensitive consumer behavior. The resulting nonlinear optimization problem is addressed using four powerful metaheuristic algorithms—Teaching-Learning-Based Optimization (TLBO), TLBO with Learning Rate, Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Particle Swarm Optimization (MOPSO). Extensive numerical simulations demonstrate the efficacy of the TLBO-based methods in achieving high-profit, low-penalty solutions, while statistical analyses confirm their robustness and superiority through the Friedman test and the Wilcoxon signed-rank test. From a managerial perspective, the model offers critical insights for aligning operational decisions with sustainability-oriented goals by demonstrating the nonlinear effects of human efficiency and product lifecycle attributes on supply chain performance. From a policy standpoint, the findings advocate for institutional mechanisms that incentivize investment in skill development, recycling, and circularity-driven design practices. Furthermore, the social relevance of this work lies in its contribution to Industry 5.0 paradigms, where inclusive, sustainable, and human-empowered production systems are prioritized. This research thus provides a robust, actionable framework for decision-makers seeking to design resilient and circular supply chains that promote long-term economic value and social welfare.
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