Multi-car elevator group supervisory control system using genetic network programming

Authors:
Lu Yu;Shingo Mabu;Tiantian Zhang;Shinji Eto;Kotaro Hirasawa
Affiliations:
Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

Citing 2
Cited 0

A Graph-Based Evolutionary Algorithm: Genetic Network Programming (GNP) and Its Extension Using Reinforcement Learning

Evolutionary Computation
A Double-Deck Elevator Group Supervisory Control System Using Genetic Network Programming

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

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Abstract

Elevator group control systems are the transportation systems for handling passengers in the buildings. With the increasing demand for high-rise buildings, Multi-Car Elevator System(MCES) where two cars operate separately and independently in an elevator shaft are attracting attention as the next novel elevator system. Genetic Network Programming (GNP), one of the evolutionary computations, can realize a rule based MCES due to its directed graph structure of the individual, which makes the system more flexible. This paper discusses MCES using GNP for the buildings with 30 floors. The performance of MCES are examined and compared with Double-Deck Elevator System(DDES).