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Group Elevator Peak Scheduling Based on Robust Optimization ModelZHANG, J. , ZONG, Q. |
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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
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. |
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