在碳政策下,对不确定的电子商务闭环供应链网络进行强有力的优化
Junyan Sun1, Xing Li2, Zihao Wang2
1School of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, Shaanxi, China. tjmsjy2003@sina.com.
Scientific reports
|October 2, 2025
概括
本研究介绍了电子商务闭环供应链的强大优化框架,解决需求,回报和中断的不确定性,以尽量降低成本和碳排放. 新的Prim-NSGAII算法提高了复杂网络优化的解决方案质量和效率.
科学领域:
- 运营研究 运营研究
- 供应链管理 供应链管理
- 环境经济学环境经济学
背景情况:
- 电子商务的增长增加了需求和回报的不确定性.
- 供应链中断被全球事件和可持续性任务所加剧.
- 现有的研究不足以解决电子商务在多种不确定性和碳政策下闭环供应链的问题.
研究的目的:
- 为电子商务闭环供应链开发一个双重目标的强大优化框架.
- 在需求,回报和破坏的不确定性下,同时最大限度地降低总成本和碳排放.
- 增强传统的多目标算法,用于复杂的网络优化.
主要方法:
- 将需求,回报和破坏的不确定性整合到一个双重目标的强大优化模型中.
- 使用了需求/回报波动的盒子不确定性和基于场景的干扰方法.
- 通过将Prim算法与NSGA-II集成,开发了Prim-NSGAII算法,以改善初始人口和解决方案质量.
主要成果:
- 拟议的模型在电子商务封闭循环供应链优化方面表现出强大的稳定性和有效性.
- 与传统的NSGA-II相比,Prim-NSGAII算法显著提高了解决方案质量 (IGD提高了39.3%,SM提高了69.1%) 和效率.
- 数值实验验证实了该模型能够平衡成本和减少碳排放的能力.
结论:
- 该研究为优化电子商务闭环供应链在复杂的不确定性中提供了一个强大的框架.
- Prim-NSGAII算法在融合和解决方案多样性方面提供了卓越的性能,用于多目标优化.
- 调查结果为碳政策与成本之间的动态关系提供了洞察力,有助于政府制定战略.
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