A study on energy consumption of elevator group supervisory control systems using genetic network programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @InProceedings{Yu:2009:ieeeSMC,
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author = "Lu Yu and Shingo Mabu and Tiantian Zhang and
Kotaro Hirasawa and Tsuyoshi Ueno",
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title = "A study on energy consumption of elevator group
supervisory control systems using genetic network
programming",
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booktitle = "IEEE International Conference on Systems, Man and
Cybernetics, SMC 2009",
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year = "2009",
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month = "11-14 " # oct,
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pages = "583--588",
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abstract = "Elevator group supervisory control system (EGSCS) is a
traffic system, where its controller manages the
elevator movement to transport passengers in buildings
efficiently. Recently, artificial intelligence (AI)
technology has been used in such complex systems.
Genetic network programming (GNP), a graph-based
evolutionary method extended from GA and GP, has been
already applied to EGSCS. On the other hand, since
energy consumption is becoming one of the greatest
challenges in the society, it should be taken as
criteria of the elevator operations. Moreover, the
elevator with maximum energy efficiency is therefore
required. Finally, the simulations show that the
elevator system has the higher energy consumption in
the light traffic, thus, some factors have been
introduced into GNP for energy saving in this paper.",
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keywords = "genetic algorithms, genetic programming, genetic
network programming, AI technology, EGSCS, GA, GNP, GP,
artificial intelligence technology, building passenger
transport, complex system, elevator group supervisory
control system, energy consumption, energy saving,
graph-based evolutionary method, maximum energy
efficiency, traffic control system, graph theory,
intelligent control, large-scale systems, lifts",
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DOI = "doi:10.1109/ICSMC.2009.5346621",
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ISSN = "1062-922X",
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notes = "Also known as \cite{5346621}",
- }
Genetic Programming entries for
Lu Yu
Shingo Mabu
Tiantian Zhang
Kotaro Hirasawa
Tsuyoshi Ueno
Citations