A New Paradigm for Assessing the Effectiveness of Up-Peak Group Control Algorithms

Elevator group control is critical to the optimal operation of elevator traffic systems under general traffic conditions. In the last 20 years, new elevator group control algorithms have become available for use under up-peak traffic conditions. These up-peak algorithms can be generally classified into three categories: static sectoring, dynamic sectoring and destination group control. It is customary to use simulation to assess the effectiveness of group control algorithms. This paper offers a new approach, which is built around numerical methods. Numerical methods can be used to objectively assess the effectiveness of an up-peak group control algorithm by subjecting the group controller to a large number of random scenarios. Each random scenario comprises a set of randomly generated passenger destinations. The performance of each scenario is recorded and the average performance of all the scenarios is used as an indicator of the effectiveness of the algorithm. The conditions under which the scenarios are run and the algorithms executed can gradually move from the fully idealised conditions to the fully realistic conditions. There are a number of benefits to this approach which will be outlined in the paper.