考虑多种运输方式的整车物流服务供应链订单分配问题

doi:10.11772/j.issn.1001-9081.2018122461

计算机应用 ›› 2019, Vol. 39 ›› Issue (6): 1836-1841.DOI: 10.11772/j.issn.1001-9081.2018122461

• 应用前沿、交叉与综合 • 上一篇下一篇

考虑多种运输方式的整车物流服务供应链订单分配问题

李丽滢, 付寒梅

辽宁工程技术大学工商管理学院, 辽宁葫芦岛 125105

收稿日期:2018-12-12 修回日期:2019-02-27 发布日期:2019-06-17 出版日期:2019-06-10
通讯作者: 付寒梅
作者简介:李丽滢(1966-),女,辽宁沈阳人,教授,博士,主要研究方向:物流路径优化、低碳供应链管理、企业战略;付寒梅(1994-),女,河南商水人,硕士研究生,主要研究方向:物流订单分配、物流路径优化。
基金资助:
辽宁省教育厅社会科学项目（LJYR006）。

Order allocation problem of vehicle logistics service supply chain considering multiple modes of transportation

LI Liying, FU Hanmei

College of Business Administration, Liaoning Technical University, Huludao Liaoning 125105, China

Received:2018-12-12 Revised:2019-02-27 Online:2019-06-17 Published:2019-06-10
Supported by:
This work is partially supported by the Social Science Foundation of Department of Education of Liaoning Province (LJYR006).

摘要/Abstract

摘要： 针对整车物流服务供应链的订单分配问题，提出了考虑多种运输方式的双层订单分配模型。首先，考虑到运输方式会影响运输成本、客户的准时送达要求等因素，建立以准时送达和最小化物流采购成本为目标的双层规划模型；其次，设计启发式算法（HA）确定各运输方式的任务量；然后，借助混合蛙跳算法（SFLA）求解各功能物流服务提供商间各运输方式的任务量分配；最后，通过不同规模的算例与遗传算法（GA）、粒子群算法（PSO）、蚁群算法（ACO）等进行求解对比。算例结果表明，与原有的成本438万元相比，所提模型得到显著优化的421万元，说明所构建模型的订单分配方案能够更有效解决整车物流的订单分配问题。实验对比表明，较传统智能算法（GA、PSO、ACO）的求解结果，两阶段的HA-SFLA算法能更快得出显著优化的结果，说明HA-SFLA算法能更好地求解考虑运输方式的双层订单分配规划模型。在满足客户送达时间要求的同时，考虑运输方式的双层订单分配模型及算法显著降低物流成本，促进物流集成商为获取更多利益而在订单分配阶段考虑运输方式。

关键词: 物流服务供应链, 订单分配, 运输方式, 双层规划, 混合蛙跳算法

Abstract: Focusing on the order allocation in vehicle logistics service supply chain, a bi-level programming model considering multiple modes of transportation was proposed. Firstly, considering that different transportation modes affect the transportation cost and the customer's on-time delivery requirement, a bi-level programming model aiming to punctual delivery and minimization of purchasing cost was established. Secondly, a Heuristic Algorithm (HA) was designed to determine the tasks of each transportation mode. Thirdly, Shuffled Frog Leaping Algorithm (SFLA) was used to solve task allocation of each transportation mode between functional logistics service providers. Finally, the solution of the proposed model was compared with those of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) through different scale examples. The results show that compared with the original purchasing cost 4.38 million yuan, the proposed model has a significantly optimized result 4.21 million yuan, which shows the order allocation scheme of the proposed model solves the order allocation problem of vehicle logistics more effectively. Experimantal results show that HA-SFLA can obtain the significantly optimized result quickly compared to GA, PSO and ACO, illustrating that HA-SFLA can solve the bi-level model considering transportation modes more efficiently. The bi-level order allocation model and algorithm considering transportation modes can reduce logistics costs while meet customer on-time requirements, making the logistics suppliers consider the transportation modes in order allocation phase to achieve more benefits.

Key words: Logistics Service Supply Chain (LSSC), order allocation, transportation mode, bi-level programming, Shuffled Frog Leaping Algorithm (SFLA)

中图分类号:

F273.1

李丽滢, 付寒梅. 考虑多种运输方式的整车物流服务供应链订单分配问题[J]. 计算机应用, 2019, 39(6): 1836-1841.

LI Liying, FU Hanmei. Order allocation problem of vehicle logistics service supply chain considering multiple modes of transportation[J]. Journal of Computer Applications, 2019, 39(6): 1836-1841.

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考虑多种运输方式的整车物流服务供应链订单分配问题

Order allocation problem of vehicle logistics service supply chain considering multiple modes of transportation

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