文章摘要
王勇,罗双,苟梦圆,罗思妤.考虑动态需求的生鲜商品物流配送优化方法研究[J].包装工程,2024,45(7):148-158.
WANG Yong,LUO Shuang,GOU Mengyuan,LUO Siyu.Fresh Commodity Logistics Distribution Optimization Considering Dynamic Demands[J].Packaging Engineering,2024,45(7):148-158.
考虑动态需求的生鲜商品物流配送优化方法研究
Fresh Commodity Logistics Distribution Optimization Considering Dynamic Demands
投稿时间:2023-10-10  
DOI:10.19554/j.cnki.1001-3563.2024.07.019
中文关键词: 生鲜商品配送  动态需求  价值损失  高斯混合聚类  改进蚁群算法
英文关键词: fresh commodity distribution  dynamic demands  value loss  Gaussian mixture clustering  improved ant colony algorithm
基金项目:国家自然科学基金(72371044,71871035);重庆市教委科学技术研究重大项目(KJZD-M202300704);重庆市自然科学基金面上项目(CSTB2022NSCQ-MSX0535);巴渝学者青年项目(YS2021058);智能物流网络重庆市重点实验室开放基金(KLILN2023ZD003)
作者单位
王勇 重庆交通大学重庆 400074
绿色物流智能技术重庆市重点实验室重庆 400074 
罗双 重庆交通大学重庆 400074 
苟梦圆 重庆交通大学重庆 400074
绿色物流智能技术重庆市重点实验室重庆 400074 
罗思妤 重庆交通大学重庆 400074 
摘要点击次数:
全文下载次数:
中文摘要:
      目的 针对生鲜商品配送过程中客户需求的变化,协调静态与动态客户需求之间的关系,合理规划路径,并降低物流总成本。方法 首先考虑客户生鲜需求的多样化温控区间、随机订单请求时间及动态需求量等因素,构建物流总成本最小化的整数规划模型。然后,设计基于高斯混合聚类的改进蚁群算法求解该模型,并提出动态需求处理策略,用于路径的再优化。其次,通过与粒子群算法、遗传算法和鲸鱼优化算法进行对比分析,验证文中设计算法的有效性。最后,以重庆市某生鲜配送网络为例,对比分析优化前后的运营指标,并探讨生鲜商品价值损失水平与物流总成本之间的关系。结果 经优化后,物流总成本下降了22.35%,其中惩罚成本、价值损失、配送成本和温控成本分别下降了39.84%、61.84%、29.80%、57.00%。结论 文中所提的模型、算法和动态需求处理策略可以合理规划配送路径,有效降低了总成本,为考虑动态需求的生鲜配送网络优化提供了参考。
英文摘要:
      The work aims to coordinate the relationship between static and dynamic customer demands in view of the changes in the customer demands for the fresh commodity distribution, and plan the path reasonably and reduce the total logistics cost. Firstly, an integer programming model was established for minimizing the total logistics cost in consideration of the diverse temperature control intervals, random order request time, and dynamic customer demands quantity. Then, an improved ant colony algorithm based on Gaussian mixture clustering was designed to solve this model, and a dynamic demands processing strategy was proposed to re-optimize routes. Next, the effectiveness of the proposed algorithm was verified through comparison with particle swarm optimization, genetic algorithm and whale optimization algorithm. Finally, with the fresh commodity distribution network in Chongqing as an example, the operational indicators before and after optimization were compared and analyzed. Besides, the relationship between the value loss level of fresh commodity and the total logistics cost was explored. After optimization, the total logistics cost decreased by 22.35%, in which the penalty cost, the value loss, distribution cost and temperature control cost reduced by 39.84%, 61.84%, 29.80% and 57.00%, respectively. The proposed model, algorithm and dynamic demands processing strategy can reasonably plan routes and effectively reduce the total cost, which provides a methodological reference for fresh commodity distribution network optimization with dynamic demands.
查看全文   查看/发表评论  下载PDF阅读器
关闭

关于我们 | 联系我们 | 投诉建议 | 隐私保护 | 用户协议

您是第21772487位访问者    渝ICP备15012534号-2

版权所有:《包装工程》编辑部 2014 All Rights Reserved

邮编:400039 电话:023-68795652 Email: designartj@126.com

    

渝公网安备 50010702501716号