抄録
Genetic Network Programming (GNP) whose gene consists of directed graphs has been proposed as a new method of evolutionary computations, and it is recently applied to the Elevator Group Supervisory Control System (EGSCS), a real world problem, to confirm its effectiveness. In the previous study, although the flow of traffic in the elevator system is known and fixed, it is changed dynamically with time in real elevator systems. Therefore, the EGSCS with an adaptive control should be studied considering such changes for practical applications. In this paper, the GNP with functional localization is applied to the EGSCS to construct such an adaptive system. In the proposed method, the switching GNP can switch the functionally localized GNPs (assigning GNPs) fitted to several kinds of traffic by detecting the change of the flow of traffic. From the simulations, the adaptability and effectiveness of the proposed method are clarified using the traffic data of a day in an office building.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings |
| ページ | 328-335 |
| ページ数 | 8 |
| 巻 | 1 |
| 出版物ステータス | Published - 2005 |
| イベント | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland 継続期間: 2005 9 2 → 2005 9 5 |
Other
| Other | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 |
|---|---|
| 市 | Edinburgh, Scotland |
| 期間 | 05/9/2 → 05/9/5 |
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ASJC Scopus subject areas
- Engineering(all)
これを引用
Elevator group supervisory control system using genetic network programming with functional localization. / Eguchi, Toru; Hirasawa, Kotaro; Furuzuki, Takayuki; Markon, Sandor.
2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings. 巻 1 2005. p. 328-335.研究成果: Conference contribution
}
TY - GEN
T1 - Elevator group supervisory control system using genetic network programming with functional localization
AU - Eguchi, Toru
AU - Hirasawa, Kotaro
AU - Furuzuki, Takayuki
AU - Markon, Sandor
PY - 2005
Y1 - 2005
N2 - Genetic Network Programming (GNP) whose gene consists of directed graphs has been proposed as a new method of evolutionary computations, and it is recently applied to the Elevator Group Supervisory Control System (EGSCS), a real world problem, to confirm its effectiveness. In the previous study, although the flow of traffic in the elevator system is known and fixed, it is changed dynamically with time in real elevator systems. Therefore, the EGSCS with an adaptive control should be studied considering such changes for practical applications. In this paper, the GNP with functional localization is applied to the EGSCS to construct such an adaptive system. In the proposed method, the switching GNP can switch the functionally localized GNPs (assigning GNPs) fitted to several kinds of traffic by detecting the change of the flow of traffic. From the simulations, the adaptability and effectiveness of the proposed method are clarified using the traffic data of a day in an office building.
AB - Genetic Network Programming (GNP) whose gene consists of directed graphs has been proposed as a new method of evolutionary computations, and it is recently applied to the Elevator Group Supervisory Control System (EGSCS), a real world problem, to confirm its effectiveness. In the previous study, although the flow of traffic in the elevator system is known and fixed, it is changed dynamically with time in real elevator systems. Therefore, the EGSCS with an adaptive control should be studied considering such changes for practical applications. In this paper, the GNP with functional localization is applied to the EGSCS to construct such an adaptive system. In the proposed method, the switching GNP can switch the functionally localized GNPs (assigning GNPs) fitted to several kinds of traffic by detecting the change of the flow of traffic. From the simulations, the adaptability and effectiveness of the proposed method are clarified using the traffic data of a day in an office building.
UR - http://www.scopus.com/inward/record.url?scp=27144473874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=27144473874&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:27144473874
SN - 0780393635
VL - 1
SP - 328
EP - 335
BT - 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings
ER -