E3S Web Conf.
Volume 53, 20182018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
|Number of page(s)||4|
|Section||Environment Engineering, Environmental Safety and Detection|
|Published online||14 September 2018|
A Intelligent Logistics Inventory Distribution Model Based On Pipeline Network And Ant Colony Algorithm
Guilin University of Technology, Guilin 541004, China
2 Guangdong provincial land and resources surveying and Mapping Institute, Guangzhou 510599, China
* Corresponding author: firstname.lastname@example.org
With the popularization and application of emerging Internet technologies such as big data and cloud computing, the traditional B2B and B2C warehousing logistics management modes have not achieved synergy between various distribution stations and suppliers, achieving “one-to-one” means a distribution station is supplied by a manufacturer, and a customer is also supplied by a distribution station. The traditional logistics industry model can no longer meet the individual needs of customers. At present, the logistics industry has a series of problems such as slow delivery, slow turnover, high cost and poor service. Based on the theoretical basis of pipeline network and smart logistics, this paper proposes a pipeline network model of intelligent logistics, and improves the ant colony algorithm to improve transportation efficiency, which provides a guarantee for the efficient operation of the intelligent logistics platform.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.