PI驱动的可持续汽车生产-运输集成优化模型与I-MOEA/D-DRA算法
Solving the Physical Internet-enabled Sustainable Production-distribution Joint Optimization for Automobile Industry by I-MOEA/D-DRA
薛瑶婷 1戢守峰 2朱国松 3戢婷婷2
作者信息
- 1. 东北大学工商管理学院,辽宁沈阳 110167;华晨宝马汽车有限公司供应链规划部,辽宁沈阳 100027
- 2. 东北大学工商管理学院,辽宁沈阳 110167
- 3. 华晨宝马汽车有限公司供应链规划部,辽宁沈阳 100027
- 折叠
摘要
物联网(physical internet,PI)驱动的机器通信从数字化生产角度为可持续汽车供应链提供了新的解决方案.从经济、环境与社会可持续三个维度全面评估了 PI驱动的可持续汽车生产-运输系统,构建了物联网环境下数字化汽车供应链的生产-运输集成优化问题多目标整数非线性模型,并设计了 一种改进的基于分解的多目标进化算法-动态资源分配(improved multi-objective evolutionary algorithm based on decomposition with dynamical resource allocation,I-MOEA/D-DRA)进行求解.该算法提出了自适应邻域选择、环境选择、局部搜索机制与基于子问题的动态规划策略来提升算法性能.基于华晨宝马公司实际运作的数值实验,验证了模型的有效性与I-MOEA/D-DRA算法的性能.
Abstract
Physical internet-enabled machines to communicate provides new solutions for sustainable supply chain from digital production.The PI-enabled automotive(PI-A)supply chain was formulated as a multi-objective integer nonlinear model and evaluated from the three dimensions of economic,environmental and social sustainability.An improved MOEA/D-DRA(I-MOEA/D-DRA)was developed to solve the practical-scale PI-A scheduling problem.The adaptive neighborhood selection,environment selection,guided local search mechanism and sub-problem solution guided dynamic programming were designed to improve the performance.The performance advantage of I-MOEA/D-DRA and the sustainable advantage of PI-A were validated by numerical experiments which were extracted from the actual operation of BMW.
关键词
生产-运输集成优化/多目标优化/I-MOEA/D-DRA算法Key words
production-distribution integrated scheduling/multiple objectives optimization/I-MOEA/D-DRA algorithm引用本文复制引用
基金项目
国家自然科学基金资助项目(71971049)
辽宁省教育厅2022年度高校基本科研项目(LJKMR20220343)
辽宁省社会科学界联合会2022年度辽宁经济社会发展立项课题(2022slybkt-029)
辽宁省社会科学规划基金重大项目(L23ZG038)
出版年
2024
NETL
NSTL
万方数据