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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.