Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society

Improved Ant Colony Algorithm in Logistics Time Optimal Path Selection based on the Positive and Negative Feedback and Neighboring Rights

Authors
Xiaochuan Guo
Corresponding Author
Xiaochuan Guo
Available Online April 2016.
DOI
https://doi.org/10.2991/emim-16.2016.291How to use a DOI?
Keywords
Ant colony algorithm; Connection weights; Negative feedback; Path Selection
Abstract
Ant colony algorithm is a new heuristic optimization algorithm suitable for solving complex combinatorial optimization problems. Traditional ant colony algorithm converges slowly, and falls into local optimal solution, this paper presents a negative feedback connection weights improved ant colony algorithm. On the basis of the core to the ant colony algorithm, according to the selection result and continue to function through a negative feedback to adjust the connection weights, in order to achieve optimal search algorithm. In this paper, the choice of the path Yuan tong Express, for example, to the shortest path is selected as the objective function, the optimization functions by negative feedback connection weight, effectively improve the convergence speed and overall performance, it can better solve the optimal path of express logistics the selection problem.
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Proceedings
6th International Conference on Electronic, Mechanical, Information and Management Society
Part of series
Advances in Computer Science Research
Publication Date
April 2016
ISBN
978-94-6252-176-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/emim-16.2016.291How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xiaochuan Guo
PY  - 2016/04
DA  - 2016/04
TI  - Improved Ant Colony Algorithm in Logistics Time Optimal Path Selection based on the Positive and Negative Feedback and Neighboring Rights
BT  - 6th International Conference on Electronic, Mechanical, Information and Management Society
PB  - Atlantis Press
SP  - 1432
EP  - 1438
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-16.2016.291
DO  - https://doi.org/10.2991/emim-16.2016.291
ID  - Guo2016/04
ER  -