Title :
The Research of Elevator Group Dynamic Scheduling During Up-peak Traffic Based on POMDP
Author :
Zong Qun ; Sun Zheng-ya
Author_Institution :
Acad. of Electr. Eng. & Autom., Tianjin Univ., China
Abstract :
Due to the existence of the uncertainty of the traffic flows in the problem of elevator group control scheduling, Markov decision processes can´t deal with the model of the elevator group control scheduling well. The model based on partially observable Markov decision processes is studied to solve this problem. With application of the feedforward neural network, which is integrated into the linear Q-learning to construct the whole algorithm for elevator group scheduling, the optimal or nearly optimal policies are obtained gradually. Compared with previous algorithms, this algorithm greatly improves the adaptability to the up-peak traffic flow.
Keywords :
Markov processes; dynamic scheduling; feedforward neural nets; learning (artificial intelligence); traffic; elevator group control scheduling; elevator group dynamic scheduling; elevator group scheduling; feedforward neural network; linear Q-learning; partially observable Markov decision processes; reinforcement learning; traffic flows; up-peak traffic flow; Automation; Communication system traffic control; Dynamic scheduling; Elevators; Intelligent control; Learning; Scheduling algorithm; Sun; Traffic control; Uncertainty; POMDP; elevator group control scheduling; linear Q-learning; reinforcement learning;
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
DOI :
10.1109/CHICC.2006.280826
