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

doi:10.11772/j.issn.1001-9081.2018122461

Abstract

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)

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

CLC Number:

F273.1

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.

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.

References

[1] 甘家华,张晋姝,王秀.货物运输结构调整:以汽车整车物流为例[J].综合运输,2018,40(7):10-14.(GAN J H, ZHANG J S, WANG X. Transportation structure adjustment of automobile vehicle logistics[J]. China Transportation Review, 2018, 40(7):10-14.)
[2] 刘伟华,季建华,周乐.两级物流服务供应链任务分配模型[J].上海交通大学学报,2008,42(9):1524-1528.(LIU W H, JI J H, ZHOU L. An order allocation model in two-echelon logistics service supply chain[J]. Journal of Shanghai Jiaotong University, 2008, 42(9):1524-1528.)
[3] 姜意扬,王勇,邓哲锋.基于LSSC的供应商选择与订单分配[J].工业工程,2011,14(3):80-86.(JIANG Y Y, WANG Y, DENG Z F. Supplier selection and order allocation based on logistics service supply chain[J]. Industrial Engineering Journal, 2011, 14(3):80-86.)
[4] 张广胜,刘伟.考虑服务时效的物流服务供应链应急任务分配[J].计算机应用,2016,36(8):2335-2339.(ZHAGN G S, LIU W. Coordinating emergency task allocation of logistics service supply chain under time-to-service[J]. Journal of Computer Applications, 2016, 36(8):2335-2339.)
[5] 李珊珊.物流服务供应链订单分配优化及其遗传算法[J].运筹与管理,2014,23(5):35-41.(LI S S. Genetic algorithm to logistics service supply chain order allocation problem[J]. Operations Research and Management Science, 2014, 23(5):35-41.)
[6] LIU W H, WU R Z, LIANG Z C, et al. Decision model for the customer order decoupling point considering order insertion scheduling with capacity and time constraints in logistics service supply chain[J]. Applied Mathematical Modeling, 2018, 54:112-135.
[7] 董鹏,宋守文.中国汽车整车物流与零部件物流的分析[J].铁路采购与物流,2014,9(8):54-55.(DONG P, SONG S W. Analysis of vehicle and parts logistics in China[J]. Railway Purchase and Logistics, 2014, 9(8):54-55.)
[8] 施国洪,钱坤.基于VMI和TPL理论的汽车整车物流的系统动力学分析[J].中国管理信息化,2009,12(20):81-85.(SHI G H, QIAN K. System dynamics analysis of vehicle logistics based on VMI and TPL theory[J]. Chain Management Informationization, 2009, 12(20):81-85.)
[9] 乔露露.汽车整车物流成本控制与绩效研究评价[D].西安:长安大学,2011:23-39.(QIAO L L. Study of automobile vehicle logistics cost control and performance evaluation[D]. Xi'an:Chang'an University, 2011:23-39.)
[10] 刘大成."公转铁"中整车物流发展的新契机[N].经济参考报,2018-10-09[2018-11-01].(LIU D C. A new opportunity for the development of vehicle logistics in the "transfer iron"[N]. Economic Reference Daily, 2018-10-09[2018-11-01].)
[11] 刘弘超,秦璐,张晋姝.基于合规运输的第三方整车物流多式联运网络优化[J].商业经济研究,2016,7(23):90-93.(LIU H C, QIN L, ZHANG J S. Optimization of third-party vehicle logistics multimodal transport network based on compliance transportation[J]. Journal of Commercial Economics, 2016, 7(23):90-93.)
[12] MASOUD S A, MASON S J. Assessing the cost impact of multiple transportation modes to enhance sustainability in an integrated, two stage, automotive supply chain[J]. Informatics, 2017, 34:72-84.
[13] 李锐,孙福明.多种运输方式的4PL多到多网络设计模型与算法[J].计算机工程与应用,2018,42(3):229-234.(LI R, SUN F M. Model and algorithm for 4PL many-to-many network design with multiple transportation modes[J]. Computer Engineering and Applications, 2018, 54(18):229-234.)
[14] 于雪峤,郎茂祥,王伟哲,等.考虑模糊需求的多式联运路径优化[J].北京交通大学学报,2018,42(3):23-29,36.(YU X Q, LANG M X, WANG W Z, et al. Multimodal transportation routing optimization considering fuzzy demands[J]. Journal of Beijing Jiaotong University, 2018, 42(3):23-29, 36.)
[15] HADDAD-SISAKHT A, RYAN S M. Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax[J]. International Journal of Production Economics, 2018, 195:118-131.
[16] EUSUFF M M, LANSEY K E. Optimization of water distribution network design using the shuffled forg leaping algorithm[J]. Journal of Water Resources Planning and Management, 2003, 129(3):210-225.
[17] 崔文华,刘晓冰,王伟,等.混合蛙跳算法研究综述[J].控制与决策,2012,27(4):481-486, 493.(CUI W H, LIU X B, WANG W,et al. Survey on shuffled frog leaping algorithm[J]. Control and Decision, 2012, 27(4):481-486, 493.)
[18] 郑仕链,楼才义,杨小牛.基于改进混合蛙跳算法的认知无线电协作频谱感知[J].物理学报,2010,59(5):3611-3617.(ZHENG S L, LOU C Y, YANG X N. Cooperative spectrum sensing for cognitive radios based on a modified shuffled frog leaping algorithm[J]. Acta Physica Sinica, 2010, 59(5):3611-3617.)