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 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.