Author(s)

Xuelian Guo ¹, Yuanyuan Li ¹, Xuefeng Liu ¹, Xiaoyu Xu ¹

Affiliation(s)

¹ Business School, Shandong University of Technology, Zibo, Shandong, 255000, China

Corresponding Author

Xuelian Guo

ABSTRACT

In recent years, with the continuous development and popularity of Internet technology, people's demand for online shopping has gradually increased, which in turn has caused scholars to pay attention to and study the problems existing in courier delivery routes. In this paper, based on the traditional vehicle routeing problem, combined with the customer's demand for time windows and considering the constraints of transport vehicle loading during the pickup and delivery process, the brainstorming optimization algorithm is used to derive the service route of Company M based on the realistic problem of Company M. The service route is designed for 35 customers by taking the shortest total distance of delivery as the goal. The calculation results show that Company M needs to send four trucks to serve 35 customers, and the designed service routes all meet the customers' requirements for time windows. This case shows that the brainstorming optimization algorithm has good performance in solving the simultaneous pickup and delivery problem with time window constraints.

KEYWORDS

Brainstorming optimization algorithm; Path optimization problem; Time window; vehicle delivery

CITE THIS PAPER

Xuelian Guo, Yuanyuan Li, Xuefeng Liu, Xiaoyu Xu, Research on Vehicle Routing Optimization for M Company Considering Time Window Constraints. Frontiers in Traffic and Transportation Engineering (2023) Vol. 3: 8-17. DOI: http://dx.doi.org/10.23977/ftte.2023.030102.

REFERENCES

[1] Dantzig G B, Ramser J H. The truck dispatching problem. Management science, 1959, 6(1): 80-91.
[2] Wu X, Li R, Chu C H, et al. Managing pharmaceuticals delivery service using a hybrid particle swarm intelligence approach. Annals of Operations Research, 2022. 308(1-2): 653-684.
[3] Peng Xu. Analysis of the Problems and Countermeasures in the Development of Modern Pharmaceutical Logistics in China. Shandong Social Sciences, 2016, (S1): 173-174.
[4] Jing Rui. Layout and Enlightenment of Pharmaceutical Logistics in Germany. Social Scientist, 2019 (03): 64-68.
[5] Jin H, He Q, He M, et al. Optimization for medical logistics robot based on model of traveling salesman problems and vehicle routing problems. International Journal of Advanced Robotic Systems, 2021. 18(3).
[6] Osvald A, Stirn L Z. A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food. Journal of food engineering, 2008, 85(2): 285-295.
[7] Han Mengyi, Ding Junwu, Chen Mengqin, et al. Optimization of emergency materials distribution path based on hybrid genetic algorithm. Science and Engineering, 2021, 21 (22): 9432-9439.
[8] Li Zhaojin, Liu Ya, Yang Zhen. Research on multimodal transportation route optimization considering order consolidation and cargo transshipment. Operations Research and Management, 2022, 31 (04): 28-34.
[9] Wang Yong, Zuo Jiaxin, Jiang Qiong, et al. Reverse logistics vehicle routing optimization based on product recovery pricing. Journal of Systems Management, 2022, 31 (02): 199-216.
[10] Alcaraz J J, Caballero-Arnaldos L, Vales-Alonso J. Rich vehicle routing problem with last-mile outsourcing decisions. Transportation Research Part E-Logistics and Transportation Review, 2019. 129: 263-286.
[11] Eshtehadi R, Demir E, Huang Y. Solving the vehicle routing problem with multi-compartment vehicles for city logistics. Computers & Operations Research, 2020. 115.
[12] Martins L D C, Tordecilla R D, Castaneda J , et al. Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation. Energies, 2021. 14(16).
[13] Tas D. Electric vehicle routing with flexible time windows: a column generation solution approach. Transportation Letters-The International Journal of Transportation Research, 2021. 13(2): 97-103.
[14] Zhang Jinliang, Li Chao. Research on Dynamic Delivery Vehicle Routing Optimization under the Influence of Carbon Emission. Chinese Management Science, 2022, 30 (09): 184-194.
[15] Li M, Tang R. Research on Optimization of Cold Chain Logistics Distribution Path of Fresh Agricultural Products. International Conference on Economy, Management and Entrepreneurship. 2019.

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