需求可拆分Milk-run与 Supply-hub协同的汽车零部件入厂物流优化

doi:10.16381/j.cnki.issn1003-207x.2019.1806

中国管理科学 ›› 2022, Vol. 30 ›› Issue (7): 59-68.doi: 10.16381/j.cnki.issn1003-207x.2019.1806

需求可拆分Milk-run与 Supply-hub协同的汽车零部件入厂物流优化

黄肖玲¹, 陈焕平¹, 高晓楠¹, 王丹¹, 刘进平¹, 陈继红²

1.大连海事大学交通运输工程学院，辽宁大连116026；2.上海海事大学交通运输学院，上海201306

收稿日期:2019-11-11 修回日期:2020-05-08 出版日期:2022-07-20 发布日期:2022-08-05
通讯作者: 黄肖玲(1962-)，女(汉族)，辽宁大连人，大连海事大学交通运输工程学院，教授，博士，研究方向：物流与供应链管理、交通运输规划与管理，Email:huangxiaoling@dlmu.edu.cn. E-mail:huangxiaoling@dlmu.edu.cn
基金资助:
国家自然科学基金资助项目(71371038，71431001，51409157)

Deliverysplit Milkrun and Supplyhub Collaborate to Optimize Automobiles Parts Inbound logistics

HUANG Xiao-ling¹, CHEN Huan-ping¹, GAO Xiao-nan¹, WANG Dan¹, LIU Jin-ping¹, CHEN Ji-hong²

1. College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China; 2. College of Transport & Communication, Shanghai Maritime University, Shanghai 201306, China

Received:2019-11-11 Revised:2020-05-08 Online:2022-07-20 Published:2022-08-05
Contact: 黄肖玲 E-mail:huangxiaoling@dlmu.edu.cn

摘要/Abstract

摘要： 受能源压力、环保要求、消费者需求日趋多样化等因素的影响，汽车制造企业改进整车制造体系、优化成本、挖掘新利润空间迫在眉睫。零部件入厂物流作为汽车物流系统中最复杂的部分，其过程优化是降低汽车制造企业物流总成本的关键。为提高汽车产业链效益，降低零部件入厂物流成本，本文采用需求可拆分Milk-run与Supply-hub协同对汽车零部件入厂物流进行优化。利用需求可拆分的Milk-run方式代替干线直运方式进行集并运输。构建了具有单边柔性时间窗的需求可拆分Milk-run模型。运用改进的Tabu Search算法对模型进行求解。通过应用分析，结果表明本文提出的方法提高了车辆的装载率，减少了派车数量与行驶里程，降低了汽车零部件入厂物流成本。

关键词: 入厂物流；单边柔性时间窗；Tabu Search；JIT

Abstract: Under the influence of energy pressure, environmental protection and the increasing diversification of consumer demand, it is urgent for automobile manufacturing enterprises to improve the manufacturing system, optimize the cost, and tap the new profit space. As the most complex part of automobile logistics system, the optimization of inbound logistics is the key to reduce the total logistics cost of automobile manufacturing enterprises.

Key words: inbound logistics; unilateral flexible time window; Tabu Search; JIT

中图分类号:

C931
O221

黄肖玲, 陈焕平, 高晓楠, 王丹, 刘进平, 陈继红. 需求可拆分Milk-run与 Supply-hub协同的汽车零部件入厂物流优化[J]. 中国管理科学, 2022, 30(7): 59-68.

HUANG Xiao-ling, CHEN Huan-ping, GAO Xiao-nan, WANG Dan, LIU Jin-ping, CHEN Ji-hong. Deliverysplit Milkrun and Supplyhub Collaborate to Optimize Automobiles Parts Inbound logistics[J]. Chinese Journal of Management Science, 2022, 30(7): 59-68.

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需求可拆分Milk-run与 Supply-hub协同的汽车零部件入厂物流优化

Deliverysplit Milkrun and Supplyhub Collaborate to Optimize Automobiles Parts Inbound logistics

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