Optimal dispatching control for elevator systems during uppeak traffic

Abstract

Abstract-In this paper we develop optimal dispatching controllers for elevator systems during uppeak traffic. An uppeak traffic period arises when the bulk of the passenger traffic is moving from the first floor up into the building (e.g., the start of a business day in an office building). The cars deliver the passengers and then return empty to the first floor to pick up more passengers. We show that the structure of the optimal dispatching policy minimizing the discounted or average passenger waiting time is a threshold-based policy. That is, the optimal policy is to dispatch an available car from the first floor when the number of passengers inside the car reaches or exceeds a threshold that depends on several factors including the passenger arrival rate, elevator performance capabilities, and the number of elevators available at the first floor. Since most elevator systems have sensors to determine the car locations and the number of passengers in each car, such a threshold policy is easily implemented. Our analysis is based on a Markov decision problem formulation with a batch service queueing model consisting of a single queue served by multiple finite-capacity bulk servers. We use dynamic programming techniques to obtain the structure of the optimal control policy and to derive some of its important properties. Several numerical examples are included to illustrate our results and to compare the optimal threshold policy to some known ad hoc approaches. Finally, since many transportation systems can be modeled as multiserver batch service queueing systems, we expect our results to be useful in controlling those systems as well.

Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

“…The reason causing this result is due to the use of "compulsory dispatch strategy" in up peak mode. Since the traffic flow in "Up Peak Time" mainly consists of those passengers emerging at lobby and heading for upper floors, the compulsory dispatch strategy would be efficient enough in this case without employing any additional constraints such as setting a dispatching threshold of the number of loaded passengers at lobby (16) . This can also explain why we did not make an improvement of the performance, even a little bit worse in "Up Peak Time" of the proposed method, while a significant improvement was obtained in two other modes as shown in Table 4.…”

Dynamic Programming on Reduced Models and Its Evaluation through Its Application to Elevator Operation Problems

“…These patterns have their singularities in this order; the up-peak traffic pattern is most singular in the sense that we can make a best guess about future passengers among all patterns. This seems to bring about an optimal rule for an up-peak traffic pattern on a certain assumption [14]. The variation in the traffic pattern makes EOPs usable as an application of DPRM, since we can vary an SI space according to a traffic pattern without modifying a model of a considered elevator system.…”

“…The considered traffic patterns are the pure down-peak and two-way patterns, since up-peak traffic patterns seem to be solved [14] and inter-floor traffic patterns usually do not matter. The availability of the number of passengers and the traffic pattern during a given period is not so expedient even for real systems [5].…”

Optimization of Group Elevator Scheduling With Advance Information

“…These methods generally require rich experiences from professionals or huge offline training efforts to achieve good results. The structure of the optimal control policy to minimize the discounted or average passenger waiting time for up-peak traffic has been studied in [1]. The elevator system is modeled as a queuing system by using stochastic processes to describe the passenger arrival process and service process, and the scheduling problem is modeled as a Markov decision problem.…”

“…In conventional elevator systems, only up and down buttons are available for hall calls, and passengers cannot specify their destinations until they enter the elevators. The systems need to make decisions in the presence of uncertainties on passenger arrival times and destinations [1]. Such decisions are sometimes unsatisfactory.…”