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Developing an incentive‐based model for efficient product recovery and reverse logistics
Business Strategy and the Environment ( IF 12.5 ) Pub Date : 2024-08-05 , DOI: 10.1002/bse.3906
Deepak Gautam 1 , Nomesh Bolia 1
Affiliation  

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.

中文翻译:


开发基于激励的模型,以实现高效的产品回收和逆向物流



本研究提出了一种符合可持续发展目标 (SDG) 11、12 和 9 的创新模型。SDG 11 强调可持续城市方面,SDG 12 侧重于负责任的消费,SDG 9 强调弹性基础设施。该模式以提高运营利润为重点,整合了强大的逆向物流网络和政策框架,以确保安全处置和环境保护。使用 CPLEX 求解器软件,我们评估了各种方法,包括基于邻近的分配、集合覆盖问题、p 中值分配和容量松弛模型,以最大限度地提高电池回收系统的盈利能力和效率。我们的研究结果强调了传统的基于邻近性的方法的局限性,强调了高级优化的必要性。场景 3,利用p ‐中值问题,成为最有利可图的问题,优化客户分配并减少与距离相关的成本。此外,我们的敏感性分析强调了收集率参数在影响客户行为和整体系统盈利能力方面的关键作用。该研究还强调了无障碍收集中心的重要性,揭示了不同客户区域的可达性差异。这些发现需要进行细致入微的分析,以确保公平的机会。其影响包括倡导战略政策,以提高收集率、优化中心可达性并促进负责任的处置,使政策制定者、行业专业人士和环境利益相关者受益。最终,这项研究有助于可持续实践,培育具有生态意识的社会,并加速实现可持续发展目标。
更新日期:2024-08-05
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