This study endeavors to integrate green supply chain and resilience proactive strategies within a closed-loop supply chain network. The research employs a three-step methodology. In the first phase, a multi-objective, multi-period, multi-node, mixed integer linear programming model (MILP) is developed. The objective of this study is to maximize resilience while minimizing both greenhouse gas (GHG) emissions and costs. The environmental footprint is assessed using the life cycle assessment (LCA) tool as part of the green supply chain strategy. To optimize resilience strategies, proximate nodes in the closed-loop supply chain network implement measures involving node criticality and inventory availability. In the second step, a novel four-valued refined multi-objective neutrosophic optimization algorithm is introduced to resolve the model. In contrast to traditional optimization approaches, neutrosophic optimization integrates elements of truth, falsity, contradictions, and uncertainty into the decision-making process. In the third phase, a case study of the smartphone supply chain is presented, advocating for the adoption of circular economy practices to prevent future waste. To assess the resilience of the model, a sensitivity analysis has been conducted, examining various key parameters associated with the market, and studying their impact on the objective function. The model's performance is validated by comparing the solution methodology with other goal programming and interactive fuzzy multi-objective methods. The results highlight the better performance of four-valued refined neutrosophic optimization, achieving 3.59 and 3.38 times greater cumulative gap reduction than other methods. The optimal solution recommends green strategies for an optimal trade-off among cost, GHG emissions, and resilience.

中文翻译：

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智能手机闭环供应链网络设计的绿色弹性模型：一种新颖的四值精细中智优化

本研究致力于将绿色供应链和弹性主动策略整合到闭环供应链网络中。该研究采用三步法。第一阶段，开发多目标、多周期、多节点、混合整数线性规划模型（MILP）。本研究的目标是最大限度地提高复原力，同时最大限度地减少温室气体 (GHG) 排放和成本。作为绿色供应链战略的一部分，使用生命周期评估（LCA）工具评估环境足迹。为了优化弹性策略，闭环供应链网络中的邻近节点实施涉及节点关键性和库存可用性的措施。第二步，引入一种新颖的四值精细多目标中智优化算法来求解模型。与传统的优化方法相比，中智优化将真、假、矛盾和不确定性的元素整合到决策过程中。在第三阶段，提出了智能手机供应链的案例研究，倡导采用循环经济实践来防止未来的浪费。为了评估模型的弹性，进行了敏感性分析，检查与市场相关的各种关键参数，并研究它们对目标函数的影响。通过将解决方案方法与其他目标规划和交互式模糊多目标方法进行比较，验证了模型的性能。结果凸显了四值精细中智优化的更好性能，比其他方法实现了 3.59 倍和 3.38 倍的累积间隙减小。最佳解决方案建议绿色战略，以在成本、温室气体排放和复原力之间实现最佳权衡。