<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper addresses the problems existing in the current two-way logistics and distribution model of rural e-commerce and proposes the study of rural e-commerce distribution efficiency with the technical support of intelligent logistics. Based on the knowledge of multi-objective optimization theory, the maximization of distribution efficiency of logistics enterprises and the maximization of demand coverage as the objective function, while the constraints are vehicle load, service time, path constraints, and finally, complete the construction of the multi-objective optimization model of rural e-commerce logistics and distribution efficiency. According to the NSGA-II algorithm with low computational complexity, fast operation speed, and good convergence, the NSGA-II algorithm is used to solve the constructed model, and then the optimal solution of rural e-commerce logistics distribution efficiency is derived. With regional logistics as the research subject, a multi-objective optimization model for rural e-commerce logistics distribution efficiency supported by intelligent logistics technology is simulated and analyzed. The data show that compared with other algorithms, the NSGAII algorithm has a smoother learning curve oscillation, while the final result of convergence (-1.473), the objective function is smaller (20.42), and the optimal total transportation time is smaller (609.22s). Finally, in order to solve the current rural e-commerce logistics and distribution problems in part, from the improvement of rural e-commerce logistics and distribution system, strengthen the rural logistics infrastructure construction of the two aspects of rural e-commerce logistics and distribution efficiency improvement strategy.</p>
</abstract>

This paper addresses the problems existing in the current two-way logistics and distribution model of rural e-commerce and proposes the study of rural e-commerce distribution efficiency with the technical support of intelligent logistics. Based on the knowledge of multi-objective optimization theory, the maximization of distribution efficiency of logistics enterprises and the maximization of demand coverage as the objective function, while the constraints are vehicle load, service time, path constraints, and finally, complete the construction of the multi-objective optimization model of rural e-commerce logistics and distribution efficiency. According to the NSGA-II algorithm with low computational complexity, fast operation speed, and good convergence, the NSGA-II algorithm is used to solve the constructed model, and then the optimal solution of rural e-commerce logistics distribution efficiency is derived. With regional logistics as the research subject, a multi-objective optimization model for rural e-commerce logistics distribution efficiency supported by intelligent logistics technology is simulated and analyzed. The data show that compared with other algorithms, the NSGAII algorithm has a smoother learning curve oscillation, while the final result of convergence (-1.473), the objective function is smaller (20.42), and the optimal total transportation time is smaller (609.22s). Finally, in order to solve the current rural e-commerce logistics and distribution problems in part, from the improvement of rural e-commerce logistics and distribution system, strengthen the rural logistics infrastructure construction of the two aspects of rural e-commerce logistics and distribution efficiency improvement strategy.

Efficiency Improvement Mechanism of Smart Logistics Technology in Rural E-commerce Logistics and Distribution

College of Business Administrations, Henan Finance University

Applied Mathematics and Nonlinear Sciences

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

This paper addresses the problems existing in the current two-way logistics and distribution model of rural e-commerce and proposes the study of rural...

Efficiency Improvement Mechanism of Smart Logistics Technology in Rural E-commerce Logistics and Distribution

Pubblicato online: 05 ago 2024

Pagine: -

Ricevuto: 19 apr 2024

Accettato: 06 lug 2024

DOI: https://doi.org/10.2478/amns-2024-2009

Parole chiave
Multi-objective optimization, NSGA-Ⅱ algorithm, Constraints, Objective function, Rural e-commerce distribution

© 2024 Xiling Yang., published by Sciendo

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

Efficiency Improvement Mechanism of Smart Logistics Technology in Rural E-commerce Logistics and Distribution

Pubblicato online: 05 ago 2024

Pagine: -

Ricevuto: 19 apr 2024

Accettato: 06 lug 2024

DOI: https://doi.org/10.2478/amns-2024-2009

Parole chiaveMulti-objective optimization, NSGA-Ⅱ algorithm, Constraints, Objective function, Rural e-commerce distribution

© 2024 Xiling Yang., published by Sciendo

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

Parole chiave
Multi-objective optimization, NSGA-Ⅱ algorithm, Constraints, Objective function, Rural e-commerce distribution