Dispatching approach optimization of elevator group control system with destination floor guidance using Fuzzy Neural Network

Aiming at the problem of uncertainty for information collection in traditional elevator group control system (EGCS), this study proposes a method about dispatching approach optimization for a new type of EGCS with destination floor guidance. The characteristic of destination floor guidance is information admixture of hall call registration and destination selection. EGCS with destination floor guidance can attain nearly complete and reliable information aggregation in advance to guide the passenger flow effectively. In order to realize the accurate prediction of input parameters, all of the hall call registrations are classified to four groups. Based on it, the optimized prediction algorithms of evaluation items are established, including the average waiting time of passengers (AWT), the average riding time of passengers (ART), rate of waiting long time of passengers (LWR), and riding power consumption (RPC). Especially, fuzzy neural network (FNN) is applied to optimize multiple objectives for realizing reasonable dispatching approach. The simulated results show that the algorithm applied in the paper improves the evaluation items by 10% at least as compared with the traditional algorithm and it indicates an excellent application to enhance the holistic capability of EGCS.