Energy saving elevator group supervisory control system with Idle Cage Assignment using Genetic Network Programming

Elevator group supervisory control system (EGSCS) is designed for managing the elevator movement to transport passengers in buildings efficiently. So far, genetic network programming which is a kind of evolutionary computation with a graph structure has been applied to such complex systems like EGSCS. On the other hand, in order to reduce the energy consumption in EGSCS, some studies have been done in our previous research, but when some cages become idle, the cages are supposed to go back to the first floor, which consumes much energy. In this paper, we use an idle cage assignment algorithm to dispatch the idle cages in a light traffic mode in order to reduce the energy consumption of EGSCS.