Deterministic Optimization Model of Elevetor Operation Problems and An Application of Branch-and-Bound Method

In this paper, we propose a framework for obtaining the optimal car service to elevator operation problems by applying branch-and-bound methods based on the deterministic optimization model. In building the model, we assume the followings: the numbers such as time and car positions are discritized, the movement of cars and passengers synchronized with discrete time, and all passengers arriving to the hall is known beforehand. In the model, the transportation of any passenger is considered as a combination of two jobs, i.e., an into-job and an out-of-job. The into-job corresponds to a passenger's getting into a car, while the out-of-job corresponds to getting out of a car. Here, the optimal car service of the problem is obtained by assigning each into-job to an appropriate car and determining the processing order of into- and out-of-jobs for each car under some constraints including the precedence conditions. In designing a BAB solution, the assignment of into-jobs to cars and the processing order of jobs on each car are taken as decision variables.It is expected that the optimal (or near-optimal) car service obtained by applying such techniques as branch-and-bound methods based on the model is helpful to estimate the effectiveness of the utilization of look-ahead information. It is also useful in valuating the performance of the existing rules for elevator operation. In the paper, by using the proposed method, the validity of an existing rule, i.e., the Call-Dispatching and Selective-Collective rule (CDSC), is examined. The results of computational experiments show that the performance of the CDSC rule is not always the optimal or near-optimal, while it reveals a practical potential, i.e., it generates rather good car services within very short time.