A double-deck elevator group supervisory control system with destination floor guidance system using genetic network programming

Lu Yu, Jin Zhou, Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, Sandor Markon

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The Elevator Group Supervisory Control Systems (EGSCS) are the control systems that systematically manage three or more elevators in order to efficiently transport the passengers in buildings. Double-deck elevators, where two elevators are connected with each other, serve passengers at two consecutive floors simultaneously. Double-deck Elevator systems (DDES) become more complex in their behavior than conventional single-deck elevator systems (SDES). Recently, Artificial Intelligence (AI) technology has been used in such complex systems. Genetic Network Programming (GNP), a graph-based evolutionary method, has been applied to EGSCS and its advantages are shown in some papers. GNP can obtain the strategy of a new hall call assignment to the optimal elevator when it performs crossover and mutation operations to judgment nodes and processing nodes. Meanwhile, Destination Floor Guidance System (DFGS) is installed in DDES, so that passengers can also input their destinations at elevator halls. In this paper, we have applied GNP to DDES and compared DFGS with normal systems. The waiting time and traveling time of DFGS are all improved because of getting more information from DFGS. The simulations showed the effectiveness of the double-deck elevators with DFGS in different building traffics.

Original languageEnglish
Pages (from-to)1115-1122+19
JournalIEEJ Transactions on Electronics, Information and Systems
Volume127
Issue number7
Publication statusPublished - 2007 Jan 1

Keywords

  • Destination floor guidance system
  • Double-deck elevator
  • Elevator group supervisory control system
  • Genetic network programming

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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