Double-deck elevator systems using genetic network programming based on variance information

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

doi:10.1109/SICE.2007.4420970

Double-deck elevator systems using genetic network programming based on variance information

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

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Double-Deck Elevator Systems (DDES) have been invented to improve the transportation capacity of elevator group systems for decades. There are several specific features in DDES due to its specific structure, i.e., two decks are vertically connected in one shaft. Even though the DDES could work well in a pure up-peak traffic pattern by cutting up to half of the stops in an elevator round trip, it becomes intractable because of the features when running in some other traffic patterns. Some solutions employing evolutionary computation methods such as genetic algorithm were also proposed in recent years. In this paper, we propose an approach of DDES using genetic network programming based on our past studies in this field.

Original language	English
Title of host publication	SICE Annual Conference, SICE 2007
Pages	163-169
Number of pages	7
DOIs	https://doi.org/10.1109/SICE.2007.4420970
Publication status	Published - 2007 Dec 1
Event	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan Duration: 2007 Sept 17 → 2007 Sept 20

Publication series

Name	Proceedings of the SICE Annual Conference

Conference

Conference	SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
Country/Territory	Japan
City	Takamatsu
Period	07/9/17 → 07/9/20

Keywords

Double-deck elevator systems
Evolutionary computation
Genetic network programming

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2007.4420970

Cite this

Zhou, J, Yu, L, Mabu, S, Hirasawa, K, Hu, J & Markon, S 2007, Double-deck elevator systems using genetic network programming based on variance information. in SICE Annual Conference, SICE 2007., 4420970, Proceedings of the SICE Annual Conference, pp. 163-169, SICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007, Takamatsu, Japan, 07/9/17. https://doi.org/10.1109/SICE.2007.4420970

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title = "Double-deck elevator systems using genetic network programming based on variance information",

abstract = "Double-Deck Elevator Systems (DDES) have been invented to improve the transportation capacity of elevator group systems for decades. There are several specific features in DDES due to its specific structure, i.e., two decks are vertically connected in one shaft. Even though the DDES could work well in a pure up-peak traffic pattern by cutting up to half of the stops in an elevator round trip, it becomes intractable because of the features when running in some other traffic patterns. Some solutions employing evolutionary computation methods such as genetic algorithm were also proposed in recent years. In this paper, we propose an approach of DDES using genetic network programming based on our past studies in this field.",

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author = "Jin Zhou and Lu Yu and Shingo Mabu and Kotaro Hirasawa and Jinglu Hu and Sandor Markon",

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AU - Zhou, Jin

AU - Yu, Lu

AU - Mabu, Shingo

AU - Hirasawa, Kotaro

AU - Hu, Jinglu

AU - Markon, Sandor

PY - 2007/12/1

Y1 - 2007/12/1

N2 - Double-Deck Elevator Systems (DDES) have been invented to improve the transportation capacity of elevator group systems for decades. There are several specific features in DDES due to its specific structure, i.e., two decks are vertically connected in one shaft. Even though the DDES could work well in a pure up-peak traffic pattern by cutting up to half of the stops in an elevator round trip, it becomes intractable because of the features when running in some other traffic patterns. Some solutions employing evolutionary computation methods such as genetic algorithm were also proposed in recent years. In this paper, we propose an approach of DDES using genetic network programming based on our past studies in this field.

AB - Double-Deck Elevator Systems (DDES) have been invented to improve the transportation capacity of elevator group systems for decades. There are several specific features in DDES due to its specific structure, i.e., two decks are vertically connected in one shaft. Even though the DDES could work well in a pure up-peak traffic pattern by cutting up to half of the stops in an elevator round trip, it becomes intractable because of the features when running in some other traffic patterns. Some solutions employing evolutionary computation methods such as genetic algorithm were also proposed in recent years. In this paper, we propose an approach of DDES using genetic network programming based on our past studies in this field.

KW - Double-deck elevator systems

KW - Evolutionary computation

KW - Genetic network programming

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Double-deck elevator systems using genetic network programming based on variance information

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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