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中国管理科学 ›› 2025, Vol. 33 ›› Issue (8): 166-176.doi: 10.16381/j.cnki.issn1003-207x.2022.1949

• • 上一篇    

PI环境下考虑保鲜努力的冷链产品生产-库存-运输联合优化模型与求解

戢守峰1, 刘红玉2(), 王丽洁1, 戢媛媛1   

  1. 1.东北大学工商管理学院,辽宁 沈阳 110167
    2.内蒙古科技大学土木工程学院,内蒙古 包头 014010
  • 收稿日期:2022-09-07 修回日期:2022-12-19 出版日期:2025-08-25 发布日期:2025-09-10
  • 通讯作者: 刘红玉 E-mail:2386471070@qq.com
  • 基金资助:
    国家自然科学基金项目(71971049);教育部人文社会科学研究项目(24YJA630033);沈阳市哲学社会科学研究中心立项重点课题(SYSK2025-JD-15);辽宁省哲学社会科学规划基金项目(L16BGL017)

Joint Optimization Model and Algorithm of Cold Chain Product Production-inventory-transportation Considering Freshness-keeping Effort in the Physical Internet

Shoufeng Ji1, Hongyu Liu2(), Lijie Wang1, Yuanyuan Ji1   

  1. 1.School of Business Administration,Northeastern University,Shenyang 110167,China
    2.School of Civil Engineering,Inner Mongolia University of Science & Technology,Baotou 014010,China
  • Received:2022-09-07 Revised:2022-12-19 Online:2025-08-25 Published:2025-09-10
  • Contact: Hongyu Liu E-mail:2386471070@qq.com

摘要:

针对传统供应链网络中物流系统为独立物流网络的问题,探讨了具有全球开放、互联特征的PI(physical internet,实物互联网)供应网络下冷链产品生产-库存-运输联合优化问题。考虑冷链产品易腐性、物流成本高等特点,在对冷链产品新鲜度度量的基础上,构建了嵌入保鲜努力函数的多工厂、多PI枢纽和多零售店的生产-库存-运输联合优化模型,并设计改进粒子群优化算法对模型求解,以沈阳东北冷鲜港的生产-库存-运输系统为例对参数进行敏感性分析,得出不同参数对保鲜努力成本和新鲜度衰减的影响,可为企业运营管理提供科学的决策参考。

关键词: 实物互联网, 保鲜努力, 新鲜度衰减, 生产-库存-运输联合优化, 改进粒子群优化算法

Abstract:

Due to the lack of collaboration and interconnections between firms, the cost and wastage are usually quite high in traditional cold chain logistics. The advent of Physical Internet has motivated us to explore the potential value of the integrated production-inventory-transportation optimization problem for cold chain products. Consequently, the production-inventory-transportation joint optimization problem considering cold chain products in Physical Internet is proposed. Considering the characteristics of perishable cold chain products and high logistics costs, the freshness-keeping efforts and the decay of freshness are integrated to the production-inventory-transportation model in Physical Internet. The relevant mixed integer linear programming model is constructed to quantify the advantage of Physical Internet. Improved particle swarm optimization is designed to solve the model. Moreover, the validity and accuracy of model and algorithm are verified by computational experiments about production-inventory-transportation system of Shenyang Northeast Cold Fresh Port. The influence of different parameters on preservation effort cost and freshness attenuation is obtained via sensitivity analysis, which can provide scientific decision-making reference for enterprise operation and management.

Key words: Physical Internet, freshness-keeping effort, freshness decay, production-inventory-transport joint optimization, improved partial swarm optimization algorithm

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