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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2013 - 9

Group Elevator Peak Scheduling Based on Robust Optimization Model

ZHANG, J. See more information about ZHANG, J. on SCOPUS See more information about ZHANG, J. on IEEExplore See more information about ZHANG, J. on Web of Science, ZONG, Q. See more information about ZONG, Q. on SCOPUS See more information about ZONG, Q. on SCOPUS See more information about ZONG, Q. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (797 KB) | Citation | Downloads: 447 | Views: 3,119

Author keywords
EGCS, intelligent control, modeling, optimal scheduling, traffic peak, uncertainty

References keywords
elevator(16), control(16), group(11), systems(10), optimization(10), system(7), scheduling(6), robust(6), research(5), method(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-08-31
Volume 13, Issue 3, Year 2013, On page(s): 51 - 58
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.03009
Web of Science Accession Number: 000326321600009
SCOPUS ID: 84884920267

Abstract
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Full text preview
Scheduling of Elevator Group Control System (EGCS) is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization) method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 6,058 TCR
SCOPUS® Citations for all references: 7,392 TCR

Web of Science® Average Citations per reference: 195 ACR
SCOPUS® Average Citations per reference: 238 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-11-23 15:34 in 194 seconds.




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