Elevator Group Supervisory Control System with Destination Floor Guidance System using Genetic Network Programming

Abstract

Genetic network programming (GNP) has been proposed as a new method of evolutionary computation. Until now, GNP has been applied to various problems and its effectiveness was clarified. Recently, the traffic in high-rise buildings becomes more and more diversified and complicated as buildings have more different functions and intelligence. To make an elevator system operate safely and efficiently for passengers, some automatic controls have been employed. Generally, Elevator Group Supervisory Control System (EGSCS) is a complex and difficult problem to solve because it is too dynamic and probabilistic. It is suitable for GNP to apply to such a system. In this paper, EGSCS with Destination Floor Guidance System (DFGS) using GNP is compared with EGSCS without DFGS, and it is shown that EGSCS with DFGS performs well compared with EGSCS without DFGS