Multi-Objective Optimization for EGCS Using Improved PSO Algorithm

In order to improve the comprehensive service level of elevator group control system (EGCS), several dynamic performance indices should be considered including average waiting time (AWT), average riding time (ART), average service time (AST), the average number of stops (ANS) and the average long waiting percent (ALWP), etc. Therefore the elevator group control is a multi-objective optimization problem that is hard to deal with. To solve this problem, an improved particle swarm optimization algorithm (IPSO) is proposed in the paper. The multi-objective (MO) optimization problem is transferred as a version of traveling salesman problem (TSP), which is dealt with by finding the optimum Hamilton cycles. The simulation results show the validity of the proposed method.