NDLI: Effects of Passengers ’ Arrival Distribution to Double-deck Elevator Group Supervisory Control Systems Using Genetic Network Programming

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Effects of Passengers ’ Arrival Distribution to Double-deck Elevator Group Supervisory Control Systems Using Genetic Network Programming

Content Provider	Semantic Scholar
Author	Zhou Shingo Kotaro Hirasawa Jing-Lu Sándor
Copyright Year	2007
Abstract	The Elevator Group Supervisory Control Systems (EGSCS) are the control systems that systematically manage three or more elevators in order to effciently transport the passengers in buildings. Double-deck elevators, where two cages are connected with each other, are expected to be the next generation elevator systems. Meanwhile, Destination Floor Guidance Systems (DFGS) are also expected in Double-Deck Elevator Systems (DDES). With these, the passengers could be served at two consecutive floors and could input their destinations at elevator halls instead of conventional systems without DFGS. Such systems become more complex than the traditional systems. Recently, Genetic Network Programming (GNP), a graph-based evolutionary method, has been applied to EGSCS of DDES with DFGS and its advantages are shown in some previous papers. GNP can obtain the strategy of a new hall call assignment to the optimal elevator because it performs crossover and mutation operations to judgment nodes and processing nodes. In the past studies the passengers’ arrival distribution has been assumed to take Exponential distribution for many years. In this paper, we have applied Erlang distribution and Binomial distribution in order to study how the passengers’ arrival distribution affects EGSCS. We have found that the passengers’ arrival distribution has great influences on EGSCS of DDES with DFGS.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.sice.jp/ia-j/papers/07IA002.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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