Authors
Hongbo Hao1, Fengzhi Dai1, 2, *
1College of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin, China
2Department of Design, Tianjin Tianke Intelligent and Manufacture Technology Co., Ltd, Tianjin, China
*Corresponding author. Email: [email protected]
Corresponding Author
Fengzhi Dai
Received 25 October 2020, Accepted 25 July 2021, Available Online 9 October 2021.
DOI
https://doi.org/10.2991/jrnal.k.210922.010How to use a DOI?
Keywords
Smart logistics; balanced/unbalanced; transportation problem; WebGIS
Abstract
The vigorous development of the logistics industry provides a solid foundation for China’s economic prosperity. However, with the concept of “smart logistics” proposed, the transformation of the logistics industry to information technology presents great challenges. Aiming at the transportation problem in logistics industry, based on the analysis of the research status at home and abroad, this paper designs a balanced/unbalanced transportation problem solving method based on Monte Carlo similarity and genetic algorithm. In this paper, Monte Carlo similarity method is introduced to design and develop a WebGIS transportation and distribution system based on genetic algorithm. This paper analyzes the information requirements, functional requirements and performance requirements of the transportation and distribution system and gives the overall architecture of the system. The system designs the database table relations and table in detail. Finally, the running test results show that the system can effectively reduce the distribution cost, increase enterprise profits and improve enterprise efficiency.
Copyright
© 2021 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).