Application of improved ant colony algorithm in vehicle scheduling problem

DOI

10.2991/jimet-15.2015.122How to use a DOI?

Keywords

Vehicle Scheduling. Ant Colony Algorithm. Pheromone.

Abstract

In this paper, the ant colony algorithms is studied, and improve the shortcomings of the algorithm, And the improved algorithm is introduced into the field of logistics transportation. Aiming at the complexity and uncertainty of logistics transportation vehicle scheduling problem, a new algorithm is designed. The experimental results show that the improved algorithm can choose the transport route, speed up the transportation speed, improve the service quality, reduce the transportation cost and increase economic benefits.

Copyright

© 2015, 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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TY  - CONF
AU  - Wang Rui
AU  - Wang Jinguo
AU  - Wang Na
PY  - 2015/12
DA  - 2015/12
TI  - Application of improved ant colony algorithm in vehicle scheduling problem
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 656
EP  - 659
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.122
DO  - 10.2991/jimet-15.2015.122
ID  - Rui2015/12
ER  -