Energy Saving Elevator Group Supervisory Control With Idle Cage Assignment Based On Genetic Network Programming

Elevator group supervisory control system (EGSCS) is designed for managing the elevator movement to transport passengers in buildings efficiently. The assignment is a kind of real-time scheduling problem for transportation systems, so the design of effective controller by mankind is very difficult. So far. Genetic Network Programming (GNP) which is a kind of evolutionary computation with a graph structure has been applied to such complex systems like EGSCS. It made an efficient improvement of EGSCS with high performance.On the other hand, with the demand of sustainable development, energy consumption of elevator systems has been investigated by many researches. In order to investigate the energy consumption in EGSCS, some studies have been done on EGSCS using GNP in this paper. From the simulation result we know that, when there are some idle cages exist, the idle cages will move back to the base floor, this movement will cost much energy because of the effect of the heavy counter. In this paper, we use an Idle Cage Assignment Algorithm in the GNP controller. We use GNP to optimize the evaluation function values while selecting an optimal floor for the idle cage. Idle cage will be dispatched to the optimal floor to reduce both the waiting time of the passengers and the energy consumption of EGSCS.