Express company’s vehicle routing optimization by multiple-dynamic saving algorithm

Junchao Liu, Wei Liu, Yuhong Liu


Purpose: According to the disorder in circulation commuting and crossover commuting of SF company which is the China’s largest private express delivery service provider, the study uses the Saving Algorithm to make the vehicle routing and resources optimized, on this basis, proposes innovative improvements with Saving Algorithm and then applies it in every distribution center of SF forming a "multi-dynamic" type of Saving Algorithm to ensure both cost savings and timeliness. This method can be generalized for all express company to get the vehicle routing optimized.

Design/methodology/approach: As the special transportation requirements of express companies, this study optimizes the vehicle route based on Saving Algorithm, uses multiple-dynamic Saving Algorithm, and considers the timeliness requirements of the express company to achieve a balance of cost and timeliness.

Findings: The main finding is that a new method proposed which there can be a balance improvement for both cost and timeliness to optimize the vehicle route of express company. Calculation example validates the effectiveness of the model established and solving method.

Practical implications: It is a widespread practice that by setting up model and parameters for the objectives, express company can maintain the balances between cost and timeliness and achieve the optimized vehicle route.

Originality/value: It proposes innovative improvements, takes SF express company as an example, with Saving Algorithm which can be applied in every distribution center of express company to ensure the balance improvement for both cost and timeliness, and has a great practical significance to the transportation network and path optimization of express companies.


express company, saving algorithm, optimization of the vehicle route, multiple-dynamic, limitation, SF company

Full Text:



Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2022

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience