Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)

Research on the Dynamic Scheduling Method of Logistics Park Based on Queuing Theory

Authors
Xuejian Zhao, Yuying Du, Zhe Sun, Chun Ying, Shuhua Tan, Zhixin Sun
Corresponding Author
Xuejian Zhao
Available Online December 2018.
DOI
10.2991/tlicsc-18.2018.35How to use a DOI?
Keywords
Logistics Park; Dynamic scheduling; Queuing theory.
Abstract

Queuing theory is a mathematical theory and method for studying the random dispersion phenomenon and the working process of a random service system, and is mainly used to solve the queuing or congestion phenomenon. This article systematically studies the logistics dispatch at the present stage. Based on this, this paper proposes a dynamic vehicle scheduling method based on queuing theory. The results show that this method can effectively solve the problem of vehicle congestion in logistics parks.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
Series
Advances in Intelligent Systems Research
Publication Date
December 2018
ISBN
10.2991/tlicsc-18.2018.35
ISSN
1951-6851
DOI
10.2991/tlicsc-18.2018.35How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xuejian Zhao
AU  - Yuying Du
AU  - Zhe Sun
AU  - Chun Ying
AU  - Shuhua Tan
AU  - Zhixin Sun
PY  - 2018/12
DA  - 2018/12
TI  - Research on the Dynamic Scheduling Method of Logistics Park Based on Queuing Theory
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 220
EP  - 227
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.35
DO  - 10.2991/tlicsc-18.2018.35
ID  - Zhao2018/12
ER  -