Genetic Algorithms in the Elevator Allocation Problem
The purpose of the work was to test the feasibility of genetic algorithms (GAs) in the landing call allocation problem of an elevator group.
In the first test case the results given by GAs were compared with two current control programs by using an elevator simulator program. In the second test case there were three different buildings which were tested by three different realisations of the same type of passenger traffic flows generated by an elevator simulation program. The results obtained are given as averages of these runs. In the second test case the GA controller was compared with the controller that proved to be better in the first test case.
According to the results, it seems that GAs would be suitable for the elevator allocation problem or to solve similar demanding real-time optimization problems. In the simulation tests performed, the average waiting time decreased achieved by GA-based controller was (evaluated with 99% confidence interval) at most 15–33%, when traffic intensity was 140% and at least 1–13%, when traffic intensity was 40%. Accordingly, when traffic intensity was nominal (100%) average waiting time was decreased by GA-controller at most 15–24% and at least 4–12%.
KeywordsGenetic Algorithm Journey Time Allocation Problem Traffic Intensity Office Building
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