Developing an incentive‐based model for efficient product recovery and reverse logistics
研究提出一个整合逆向物流网络与政策框架的激励模型，通过CPLEX求解器评估多种方法，发现p-中值问题在电池回收中最优，并强调收集率对客户行为和利润的关键影响，为政策制定者和行业从业者提供指导。
Abstract This study presents an inventive model aligning with sustainable development goals (SDGs) 11, 12, and 9. SDG 11 emphasizes sustainable urban aspects, SDG 12 centers on responsible consumption, and SDG 9 highlights resilient infrastructure. Focused on enhancing operational profits, the model integrates a robust reverse logistics network and policy framework to ensure safe disposal and environmental preservation. Employing the CPLEX solver software, we evaluated various methodologies, including proximity‐based allocation, set covering problems, p‐median allocation, and capacity‐relaxed models, to maximize profitability and efficiency in battery return systems. Our findings underscored the limitations of conventional proximity‐based methods, emphasizing the necessity of advanced optimization. Scenario 3, utilizing the p ‐median problem, emerged as the most profitable, optimizing customer allocation and reducing distance‐related costs. Additionally, our sensitivity analysis highlighted the collection rate parameter's pivotal role in influencing customer behavior and overall system profitability. The study also emphasizes the significance of accessible collection centers, revealing disparities in accessibility across customer zones. These findings call for nuanced analyses to ensure equitable access. Implications include advocating for strategic policies to enhance collection rates, optimize center accessibility, and promote responsible disposal, benefiting policymakers, industry professionals, and environmental stakeholders. Ultimately, this research contributes to sustainable practices, fostering eco‐conscious societies, and accelerating progress toward SDGs.