Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics

Simulation and analysis of a large police reasonable scheduling model

Authors
Yuzhi Wang
Corresponding Author
Yuzhi Wang
Available Online June 2015.
DOI
https://doi.org/10.2991/icecee-15.2015.205How to use a DOI?
Keywords
police scheduling; police vehicle; particle swarm optimization algorithm
Abstract
large police scheduling model is the key to ensure the smooth progress of the police work. In view of the traditional large police reasonable scheduling model, invulnerability and robustness is not good, the paper presented a large police reasonable scheduling model based on the Internet of things technology. In the process of police scheduling, RIFD technology is combined with GPS technology to achieve automatic data acquisition for police vehicle in remote and real-time, utilization efficiency maximization of police vehicles is used as the objective function to establish the model of scheduling, particle swarm optimization algorithm is adopted for the nonlinear objective function to find the optimal solution and obtain scheduling strategy. The simulation experiments show that, with the large police reasonable scheduling model for police vehicle scheduling, can effectively improve police vehicle utilization efficiency, shorten the response time, ensure the response speed.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
June 2015
ISBN
978-94-62520-81-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/icecee-15.2015.205How 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  - Yuzhi Wang
PY  - 2015/06
DA  - 2015/06
TI  - Simulation and analysis of a large police reasonable scheduling model
PB  - Atlantis Press
SP  - 1089
EP  - 1092
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.205
DO  - https://doi.org/10.2991/icecee-15.2015.205
ID  - Wang2015/06
ER  -