Assignment strategy selection for multi-car elevator group control using reinforcement learning

2012 ◽  
Vol 3 (2) ◽  
pp. 163 ◽  
Author(s):  
Taichi Uraji ◽  
Kenichi Takahashi
Author(s):  
Jin Zhou ◽  
◽  
Lu Yu ◽  
Shingo Mabu ◽  
Kaoru Shimada ◽  
...  

In order to increase the transportation capability of elevator group systems in high-rise buildings without adding elevator installation space, double-deck elevator systems (DDES) is developed as one of the next generation elevator group control systems. Artificial intelligence (AI) technologies have been employed to find some efficient solutions in the elevator group control systems during the late 20th century. Genetic Network Programming (GNP), a new evolutionary computation method, has been employed as the elevator group control system controller in some studies of recent years. Moreover, reinforcement learning (RL) has been also found to be useful for more improvements of elevator group control performances when it is combined with GNP. In this paper, we proposed a new approach of DDES using GNP with RL, and did some experiments on a simulated elevator group control system of a typical office building to evaluate its applicability and efficiency. Simulation results show that the DDES using GNP with RL performs better than the one without RL in regular and down-peak time, while both of them outperforms a conventional approach and a heuristic approach in all three traffic patterns.


2012 ◽  
Vol 132 (11) ◽  
pp. 1016-1023 ◽  
Author(s):  
Shingo Kobori ◽  
Naohiko Suzuki ◽  
Masafumi Iwata ◽  
Sakurako Yamashita

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