Order Dispatching and Routing for Decentralized Joint Distribution Considering Empty-loading Losses

doi:10.3969/j.issn.1007-7375.230228

Abstract

Abstract: The high empty-loading rate in logistics activities may result from unreasonable routing and insufficient cooperation among enterprises. Joint distribution is an effective mode to reduce empty-loading losses. However, under the condition of decentralized joint distribution, logistics enterprises may choose the routes with minimum cost based on the assigned orders, resulting in an increase in empty-loading losses of the joint distribution alliance. This study investigates order dispatching and routing for decentralized joint distribution considering empty-loading losses. A definition of empty-loading losses is given firstly. Then, with the trade-off between the objectives of minimizing cost and empty-loading losses in the entire distribution process, an order dispatching strategy is proposed based on the characteristics of decentralized joint distribution mode, and the order dispatching and routing optimization models are developed. A precise algorithm based on epsilon constraint method, an improved MOPSO (Multiple Objective Particle Swarm Optimization) algorithm, and a polynomial-time fast algorithm are developed to solve the problem. The effectiveness of the proposed algorithms is verified based on numerical instances. Analysis results indicate that even if logistics companies pursue cost minimization, the proposed order dispatching strategy can achieve results similar to global optimization.

Key words: decentralized joint distribution, empty-loading losses, order dispatching, vehicle routing, multi-objective optimization

CLC Number:

F407.47
U116

ZHANG Meng, SUN Lulu, SU Bing, WANG Nengmin. Order Dispatching and Routing for Decentralized Joint Distribution Considering Empty-loading Losses[J]. Industrial Engineering Journal, 2024, 27(2): 107-118,137.

References

[1] WANG N, JIANG Q, JIANG B, et al. Enterprises’ green growth model and value chain reconstruction[M]. Singapore: Springer, 2022.
[2] SHI W, WANG N, ZHANG M, et al. A bi-objective pollution routing optimisation problem with decentralised cooperation and split delivery[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(11): 12357-12371
[3] DANTZIG G, RAMSER J. The truck dispatching problem[J]. Management Science, 1959, 6: 80-91
[4] WANG K, SHAO Y, ZHOU W. Matheuristic for a two-echelon capacitated vehicle routing problem with environmental considerations in city logistics service[J]. Transportation Research Part D: Transport and Environment, 2017, 57: 262-276
[5] DUHAMEL C, LACOMME P, QUILLIOT A, et al. A multi-start evolutionary local search for the two-dimensional loading capacitated vehicle routing problem[J]. Computers & Operations Research, 2011, 38(3): 617-640
[6] PUREZA V, MORABITO R, REIMANN M. Vehicle routing with multiple deliverymen: modeling and heuristic approaches for the VRPTW[J]. European Journal of Operational Research, 2012, 218(3): 636-647
[7] NASRI, M, HAFIDI I, METRANE A. Multithreading parallel robust approach for the VRPTW with uncertain service and travel times[J]. Symmetry, 2020, 13(1): 36
[8] ZHANG J, LAM W, CHEN Y. On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows[J]. European Journal of Operational Research, 2016, 249(1): 144-154
[9] WANG Y, ZHANG J, ASSOGBA K, et al. Collaboration and transportation resource sharing in multiple centers vehicle routing optimization with delivery and pickup[J]. Knowledge-Based Systems, 2018, 160: 296-310
[10] ALINAGHIAN M, SHOKOUHI N. Multi-depot multi-compartment vehicle routing problem, solved by a hybrid adaptive large neighborhood search[J]. Omega, 2018, 76: 85-99
[11] LIU R, JIANG Z. Task selection and routing problems in collaborative truckload transportation[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46(6): 1071-1085
[12] WANG Y, ZHANG S, ASSOGBA K, et al. Economic and environmental evaluations in the two-echelon collaborative multiple centers vehicle routing optimization[J]. Journal of Cleaner Production, 2018, 197: 443-461
[13] FERNÁNDEZ E, ROCA-RIU M, SPERANZA M G. The shared customer collaboration vehicle routing problem[J]. European Journal of Operational Research, 2018, 265(3): 1078-1093
[14] LI J, LI Y, PARDALOS P M. Multi-depot vehicle routing problem with time windows under shared depot resources[J]. Journal of Combinatorial Optimization, 2016, 31(2): 515-532
[15] 刘家利, 马祖军. 存在车辆租赁及共享且有时间窗的多配送中心开环VRP[J]. 系统工程理论与实践, 2013, 33(3): 666-675
LIU Jiali, MA Zujun. Multi-depot open vehicle routing problem with time windows based on vehicle leasing and sharing[J]. Systems Engineering—Theory & Practice, 2013, 33(3): 666-675
[16] 饶卫振, 段忠菲, 王炳成, 等. 协作车辆路径问题距离和能耗节约量理论边界研究[J]. 系统管理学报, 2019, 28(4): 697-707
RAO Weizhen, DUAN Zhongfei, WANG Bingcheng, et al. Theoretical bound of savings on distance and fuel consumption in the collaborative vehicle routing problem[J]. Journal of Systems & Management, 2019, 28(4): 697-707
[17] BOMPADRE A, DROR M, ORLIN J B. Improved bounds for vehicle routing solutions[J]. Discrete Optimization, 2006, 3(4): 299-316
[18] WANG N, CUI W, ZHANG M, et al. Routing optimization for medical waste collection considering infectious risk and multiple disposal centers[J]. Expert Systems With Applications, 2023, 234: 121035
[19] 张萌, 王能民. 重大事故规避的危险品运输车辆路径优化研究[J]. 运筹与管理, 2018, 27(8): 1-9
ZHANG Meng, WANG Nengmin. Research on vehicle routing for hazardous materials transportation based on catastrophe avoidance[J]. Operations Research and Management Science, 2018, 27(8): 1-9
[20] ZHANG M, WANG N, HE Z, et al. Vehicle routing optimization for hazmat shipments considering catastrophe avoidance and failed edges[J]. Transportation Research Part E: Logistics and Transportation Review, 2021, 150: 102337
[21] ZHANG M, WANG N, HE Z, et al. Bi-objective vehicle routing for hazardous materials transportation with actual load dependent risks and considering the risk of each vehicle[J]. IEEE Transactions on Engineering Management, 2019, 66(3): 429-442
[22] 王振, 郭健全. 模糊环境下考虑供应中断的再制造闭环供应链研究[J]. 工业工程, 2021, 24(1): 140-146
WANG Zhen, GUO Jianquan. Research on remanufacturing closed-loop supply chain considering supply disruption in uncertain environment[J]. Industrial Engineering Journal, 2021, 24(1): 140-146
[23] 胡小建, 袁丁. 基于鱼骨型仓库布局的多车拣选路径问题优化[J]. 工业工程, 2022, 25(1): 45-53
HU Xiaojian, YUAN Ding. An optimization of multi-vehicle picking routing problem based on fishbone warehouse layout[J]. Industrial Engineering Journal, 2022, 25(1): 45-53
[24] 徐韬, 祝烨, 谢晓忠, 等. 基于全过程的偶发性拥堵消散时间预测模型[J]. 工业工程, 2022, 25(3): 157-163
XU Tao, ZHU Ye, XIE Xiaozhong, et al. A prediction model of occasional congestion dissipation time based on the whole process[J]. Industrial Engineering Journal, 2022, 25(3): 157-163
[25] HOOGEVEEN J. Analysis of Christofides’ heuristic: Some paths are more difficult than cycles[J]. Operations Research Letters, 1991, 10(5): 291-295