Application of improved ant colony algorithm in vehicle scheduling problem

DOI

10.2991/icadme-15.2015.391How 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  - Jinguo Wang
AU  - Na Wang
AU  - Haichun Ma
PY  - 2015/10
DA  - 2015/10
TI  - Application of improved ant colony algorithm in vehicle scheduling problem
BT  - Proceedings of the 5th International Conference on Advanced Design and Manufacturing Engineering
PB  - Atlantis Press
SP  - 2095
EP  - 2098
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-15.2015.391
DO  - 10.2991/icadme-15.2015.391
ID  - Wang2015/10
ER  -