A Queue Dispatch Optimizing Method for Elevator Traffic System

Jian Liu; Ting Zhang; Jin Xiang Pian; Feng Yan Han; Li Wang; Jun Xie

doi:10.4028/www.scientific.net/AMM.182-183.1919

Paper Titles

Data Hiding Based on Noise-Balanced Error Diffusion in Color Image
p.1900

F- Rough Information Fusion and its Feature Recognition
p.1904

Using a Compass for the Localization of a Robot with PID Control
p.1910

The Research of Image Registration Method Based on the Genetic Algorithm
p.1916

A Queue Dispatch Optimizing Method for Elevator Traffic System
p.1919

The Research on Object Recognition from Occluded Images
p.1924

An Improved Self-Learning Scene Matching Algorithm
p.1928

An Analysis of Archiving Strategies in Web Archive
p.1933

Research and Implementation of Malicious Code Behavior Analysis
p.1938

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183A Queue Dispatch Optimizing Method for Elevator...

A Queue Dispatch Optimizing Method for Elevator Traffic System

Abstract:

In this paper, a new method is presented to optimize the elevator traffic system based on queue model. The application of this method is studied in detail. Parameters for the elevator running including number of elevator passenger, average waiting time and arriving ratio, and the relationships between them have been analyzed as well. Therefore, the dispatching of elevator dynamic partition can be done. The actual data of rush hours are used for simulation tests. The simulation results show that this method has good performance. The method is a more practical control strategy especially in rush hours.

You might also be interested in these eBooks

Applied Mechanics and Mechatronics Automation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

1919-1923

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.1919

Citation:

Cite this paper

Online since:

June 2012

Authors:

Jian Liu, Ting Zhang, Jin Xiang Pian, Feng Yan Han, Li Wang, Jun Xie

Keywords:

Elevator Traffic System, Queue Model, Simulation, Threshold

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Sharif. Lift and escalator energy consumption: Transportation Systems in Buildings. Vol. 13( 2000), pp.102-108.

Google Scholar

[2] Mengyuke: The Foundation and Application with the Queuing Theory(Tongji University Press, Shang Hai 1989).

Google Scholar

[3] Huaxing,: Queuing Theory and Random Service System(Shanghai Translation Publishing Company, Shang Hai 1987).

Google Scholar

[4] Albert So, Gorman Cheng, Wilson Suen and Alec Leung. Elevator performance evaluation in two numbers: Elevator World. Vol. 1(2005), pp.102-105.

Google Scholar

[5] Gina Barney. Vertical transportation in tall buildings: Elevator World. Vol. 5 (2003), pp.66-75.

Google Scholar

[6] Peng kerong, Zhang huiqiao and Lin tianyi: Analysis, Design and Control of the Elevator Traffic(China Architecture and Building Press, Beijing 1993).

Google Scholar

[7] N. Takahashi,T. Yamada,D. Miyagi and S. Markon. Basic study of optimal design of linear motor for rope-less elevator: IEEE Dept. of Electron. Eng. Vol. 7-10 (2008), pp.202-203.

DOI: 10.1049/cp:20080261

Google Scholar

[8] T. Tobita, A. Fujino, K. Segawa,K. Yoneda and Y. Ichikawa. A parameter tuning method for an elevator group control system: IEEE IECON. Vol. 2 (1996), pp.823-828.

DOI: 10.1109/iecon.1996.565984

Google Scholar

[9] Liujian and Liangyandong. Neural network control of the elevator running: Journal of Shenyang Jianzhu Engineering School. Vol. 7 (1999), pp.289-292.

Google Scholar

[10] Zhu Dewen and Liu Jian. The research and trend for elevator traffic statistic propertics: International Conference on Model and Simulation in Distributed Applications. Vol. 6 (2001), pp.199-204.

Google Scholar

[11] Manhew Brand and Daniel Nikovski. Optimal parking of elevator cars in supervisery group control: IEEE Transacions on Systems, Man, and Cybernetics . Vol. part B (2003), pp.212-219.

Google Scholar