Multicar Elevator Group Supervisory Control System using Genetic Network Programming

摘要

Elevator group control systems are the transportation systems for handling passengers in the buildings. With the increasing demand for high-rise buildings, it becomes important to improve the elevator service. The multicar elevators consist of plural cars in a single elevator shaft. It contributes to the improvement in passengers' handling capacity, while allowing the reduction of the space occupied in the building. In contrast with traditional elevator systems, the cars can no longer operate freely, where there are several restrictions on their available movements. This requires a more difficult control including stochastic scheduling with high combinatorial complexity in order to make the system more flexible. At present, lots of buildings with more than 40 floors are being built, which are usually divided into several zones served by local elevator groups. In addition, the cars should be operated at equal time intervals, especially in such a building with multicar elevator systems (MCES) in order to obtain its good performance. Genetic network programming (GNP), one of the evolutionary computations, can realize a rule-based MCES due to its directed graph structure of the individual, which makes the system more flexible. This paper discusses MCES using GNP in high-rise buildings. Also, the positions of elevators are considered to avoid the bunching phenomenon. The performance of MCES is studied and compared with single-deck elevator system (SDES) and double-deck elevator system (DDES).