Design and implementation of an adaptive dispatching controller for elevator systems during uppeak traffic

We design a dispatching controller for elevator systems during uppeak passenger traffic with the ability to adapt to changing operating conditions. The design of this controller is motivated by our previous paper where we proved that for a queuing model of the uppeak dispatching problem a threshold policy is optimal (in the sense of minimizing the average passenger waiting time) with threshold parameters that depend on the passenger arrival rate. The controller, which we call the concurrent estimation dispatching algorithm (CEDA), uses concurrent estimation techniques for discrete-event systems. The CEDA allows us to observe the elevator system while it operates under some arbitrary thresholds, and concurrently estimate, in an unobtrusive way, what the waiting time would have been had the system operated under a set of different thresholds. These concurrently estimated waiting times are used to adapt the operating thresholds to match the elevator service rate to a changing passenger arrival rate. Implementation issues relating to the limited state information provided by actual elevator systems are resolved in a way that maintains modest computational requirements and avoids the need for supplemental sensors beyond those already typically provided. Numerical performance results show the advantages of the CEDA over currently used dispatching algorithms for uppeak.