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<p>With the change in shopping methods, people have higher and higher requirements for e-commerce logistics transportation. In this paper, we first briefly study the dynamic vehicle path problem under pickup and delivery mixture and determine the modeling idea of regular path adjustment strategy. Then, based on the constraints of vehicle access rules, travel time, vehicle continuity, loading capacity ceiling, dynamic vehicle path adjustment, etc., a mathematical model to minimize the total cost consisting of vehicle call cost, travel cost, and time window penalty cost together is constructed. Finally, a single-objective optimization with the total vehicle distance as the objective is performed on the original data, and the interrelationship between the objectives in the score MOMDVRP algorithm is solved for the optimal route scheme. In the route of the optimal compromise scheme, the distance of each vehicle, although not reaching the equilibrium degree in the social scheme, is much better than the economic scheme and the environmental scheme, and the difference between the longest drive and the shortest drive is 1.47km, which is about 28.79% and 69.9% less than the difference between the economic scheme and the environmental scheme of 2.171km and 495km, and each objective has reached a more balanced state. It is of great practical significance to study the optimization of the shared path of e-commerce logistics transportation resources.</p>
</abstract>

With the change in shopping methods, people have higher and higher requirements for e-commerce logistics transportation. In this paper, we first briefly study the dynamic vehicle path problem under pickup and delivery mixture and determine the modeling idea of regular path adjustment strategy. Then, based on the constraints of vehicle access rules, travel time, vehicle continuity, loading capacity ceiling, dynamic vehicle path adjustment, etc., a mathematical model to minimize the total cost consisting of vehicle call cost, travel cost, and time window penalty cost together is constructed. Finally, a single-objective optimization with the total vehicle distance as the objective is performed on the original data, and the interrelationship between the objectives in the score MOMDVRP algorithm is solved for the optimal route scheme. In the route of the optimal compromise scheme, the distance of each vehicle, although not reaching the equilibrium degree in the social scheme, is much better than the economic scheme and the environmental scheme, and the difference between the longest drive and the shortest drive is 1.47km, which is about 28.79% and 69.9% less than the difference between the economic scheme and the environmental scheme of 2.171km and 495km, and each objective has reached a more balanced state. It is of great practical significance to study the optimization of the shared path of e-commerce logistics transportation resources.

Analysis of vehicle paths for sharing e-commerce logistics resources in China

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Analysis of vehicle paths for sharing e-commerce logistics resources in China"}

With the change in shopping methods, people have higher and higher requirements for e-commerce logistics transportation. In this paper, we first briefly study...

Analysis of vehicle paths for sharing e-commerce logistics resources in China

Online veröffentlicht: 20. Sept. 2023

Seitenbereich: -

Eingereicht: 20. Dez. 2022

Akzeptiert: 31. März 2023

DOI: https://doi.org/10.2478/amns.2023.2.00352

Schlüsselwörter
Vehicle path optimization, MOPSO-MOTS algorithm, PSO-TS algorithm, E-commerce logistics, Dynamic demand

© 2023 Feng Xie, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of vehicle paths for sharing e-commerce logistics resources in China

Online veröffentlicht: 20. Sept. 2023

Seitenbereich: -

Eingereicht: 20. Dez. 2022

Akzeptiert: 31. März 2023

DOI: https://doi.org/10.2478/amns.2023.2.00352

SchlüsselwörterVehicle path optimization, MOPSO-MOTS algorithm, PSO-TS algorithm, E-commerce logistics, Dynamic demand

© 2023 Feng Xie, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Vehicle path optimization, MOPSO-MOTS algorithm, PSO-TS algorithm, E-commerce logistics, Dynamic demand