This paper presents a new modeling of elevator group intelligent scheduling system with destination floor guidance. The traditional input mode of separate hall call registration and the destination selection is improved to a single-input mode. On this basis, dynamic partition method in up-peak traffic is studied. This method means dynamically adjust division of floor region based on flow rate and distribution of passenger. Dynamic programming algorithm is used to solve this problem. Through regroupment and classification for ensemble of hall call communication, prediction of multi-objective evaluation items is proposed. Fuzzy Neural Network is constructed and applied further to realize the optimal scheduling policy. Simulated results show that the presented elevator model is effective and the optimized scheduling algorithm has advantaged improvement for overall performance of elevator system.
['Suying Yang', 'Jianzhe Tai', 'Cheng Shao']
Dynamic Partition of Elevator Group Control System with Destination Floor Guidance in Up-peak Traffic