A Genetic Algorithm for Controlling Elevator Group Systems
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Expert Systems with Applications: An International Journal
A Double-Deck Elevator Group Supervisory Control System Using Genetic Network Programming
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Design and implementation of a fuzzy elevator group control system
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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High-rise buildings require the installation of complex elevator group control systems (EGCSs). In vertical transportation, when a passenger makes a hall call by pressing a landing call button installed at the floor and located near the cars of the elevator group, the EGCS must allocate one of the cars of the group to the hall call. We develop a particle swarm optimization (PSO) algorithm to deal with this car-call allocation problem. The PSO algorithm is compared to other soft computing techniques such as genetic algorithm and tabu search approaches that have been proved as efficient algorithms for this problem. The proposed PSO algorithm was tested in high-rise buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars. Results from trials show that the proposed PSO algorithm results in better average journey times and computational times compared to genetic and tabu search approaches.