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JACIII Vol.10 No.3 pp. 385-394
doi: 10.20965/jaciii.2006.p0385
(2006)

Paper:

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Elevator Group Supervisory Control System Using Genetic Network Programming with Functional Localization

Toru Eguchi*, Jin Zhou*, Shinji Eto*, Kotaro Hirasawa*,
Jinglu Hu*, and Sandor Markon**

*Graduate School of Information, Production and Systems, Waseda University, Hibikino 2-7, Wakamatsu-ku, Kitakyushu, Fukuoka 803-0135, Japan

**The Product Development HQ of Fujitec Co. Ltd., 1-28-10 Sho, Ibaraki, Osaka, Japan

Received:
May 9, 2005
Accepted:
November 9, 2005
Published:
May 20, 2006
Creative Commons License
Keywords:
elevator group supervisory control system, evolutionary computation, genetic network programming, functional localization, real-coded genetic algorithm
Abstract
Genetic Network Programming (GNP) having a directed graph structure has been proposed as a new method of evolutionary computation. Recently, GNP has been applied to elevator group supervisory control system (EGSCS), a real-world problem, to demonstrate its applicability and effectiveness. Its previous study considers the known and fixed traffic flow, however, it is changed dynamically with time in real elevator systems. Therefore, an EGSCS with dynamic adaptive control considering such changes should be studied for practical applications. In this paper, we have applied GNP with functional localization to an EGSCS to construct such an adaptive system. In our proposal, the switching GNP can switch the functionally localized GNPs (assigning GNPs) based on the special traffic. Simulation confirmed the adaptability and effectiveness of our proposal in daily office-building traffic.
Cite this article as:
T. Eguchi, J. Zhou, S. Eto, K. Hirasawa, J. Hu, and S. Markon, “Elevator Group Supervisory Control System Using Genetic Network Programming with Functional Localization,” J. Adv. Comput. Intell. Intell. Inform., Vol.10 No.3, pp. 385-394, 2006.
Data files:
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