Elevator group scheduling for peak flows based on Adjustable Robust Optimization model

Group elevator scheduling has received more attention with the increase demand of high-rise buildings. The key factor which affects the transportation performance's further improvement is the uncertainty of traffic flow. Moreover, peak flows are rather common in buildings, while their uncertainties aren't considered by most algorithms, that could result in larger scheduling price. It's feasible to solve the problem of uncertain peak flows' dispatching with the method of Adjustable Robust Optimization (ARO). In this paper, ARO theory is put into practice, an ARO model for peak flows of Elevator Group Control System (EGCS) is built, the idea of modeling is shown, and an ARO dispatching approach is proposed. Simulation results demonstrate the validity of the approach. Finally, future trends of ARO group scheduling are summarized.