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An elevator group supervisory control system is used to supervise multiple elevators, ensuring that they are operated efficiently. A conventional system aims at reducing average waiting time, although recently requests by elevator users have focused not only o n reducing average waiting time, but also o n reducing the riding time, the number of passengers, etc. Therefore the authors developed a new elevator group super-visory control system which improves plural control objects according to users' requests. The system effectiveness is confirmed by simulations.

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This paper describes an on-line tuning method of control parameters for a multiobjective elevator group control system.To adopt a control parameter to each building, a conventional system tunes it using a combined method of a learning function and a built-in simulator. However, an increase of tuning time, caused by the addition of control parameters, can become a serious problem. The proposed method can restrict search points by using macro knowledge of the system domain. Then, tuning time and tuning accuracy are wellbalanced.Computer simulations show its quick settling and good tuning results; actual field data got with the system verify the findings.