Elevator group supervisory control system using genetic network programming - Ranking processing and node function optimization

Toru Eguchi, Kotaro Hirasawa, Jinglu Hu, Sandor Markon

研究成果: Paper査読

抄録

Genetic Network Programming (GNP) has been proposed as a new method of evolutionary computations. Recently, GNP is applied to Elevator Group Supervisory Control System (EGSCS), that is, a benchmark of real world applications and its effectiveness is clarified. The EGSCS using GNP in the previous studies can control the elevator system using the conventional node functions. However, they do not have enough flexibility and generality for some uncertain factors due to the various different conditions in elevator systems. In this paper, several new frameworks of GNP for EGSCS are proposed in order to overcome the above problem considering the ranking calculation of elevators and node function optimization based on Real-coded GA. In the simulations, it is clarified that the proposed method can obtain better performances than the conventional methods.

本文言語English
ページ1-6
ページ数6
出版ステータスPublished - 2005 12 1
イベントSICE Annual Conference 2005 - Okayama, Japan
継続期間: 2005 8 82005 8 10

Conference

ConferenceSICE Annual Conference 2005
CountryJapan
CityOkayama
Period05/8/805/8/10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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