a double-deck elevator systems controller with idle cage assignment algorithm using genetic network programming
Many studies on Double-Deck Elevator Systems (DDES) have been done for exploring more ecient algorithms to improve the system transportation capacity, especially in a heavy trac mode. The main idea of these algorithms is to decrease the number of stops during a round trip by grouping the passengers with the same destination as much as possible. How to dispatch idle cages, which is seldom considered in the heavy trac mode, becomes important when developing the controller of DDES. In this paper, we propose a DDES controller with idle cage assignment algorithm using Genetic Network Programming (GNP) for a light traffic mode, which is based on a timer and event-driven hybrid model. To verify the effeciency and effectiveness of the proposed method, some experiments have been done under a special down-peak pattern.
double-deck elevator systems genetic network programming evolutionary computation