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 door settings at the same time. Additionally, an on-line parameter tuning method using genetic algorithms is proposed. The floor attribute control method needs several dozen control parameters to be tuned according to each building´s traffic, and the proposed method can do it. The elitist-preserving strategy is an effective way to keep control stability. A diversity-recovering operation, which initializes population, excluding the elitist individual, when traffic flow data have changed, improves the following ability for transitions of utilized conditions