An elevator group control system with floor attribute control method and system optimization using genetic algorithms

A new concept is proposed for an elevator group control system which can change control settings according to individual floor utilization situations. The floor attribute based control method uses a combination of floor attribute based evaluation and car attribute based evaluation. Computer simulations show it can improve multiple preferential floor simulations at the same time. Additionally, an on-line parameter tuning method using genetic algorithms is proposed. The floor attribute control method needs some dozens of control parameters to be tuned according to each building´s traffic, and the proposed method can do it. The elitest preserving strategy is an effective way to keep control stability. A diversity recovering operation, which initializes population, excluding the elitest individual when traffic flow data have changed, improves the following ability for transitions of utilized conditions