Multi-objective Optimization Method For Elevator Group Control System

With the increase of the high-rise building, the elevator is used more and more widely, in order to improve the quality of service, shorten the waiting time and the rising time, reduce the energy consumption, a optimization control system for schedule elevators is need to design reasonably. This system is called the elevator group control system. How to choose the appropriate scheduling algorithm to make multiple elevators operate reasonably is one of the important problems for solution.In this paper, for multi-objective optimization problems of the elevator group control system, according to the elevator group control system optimization control strategy, a PSO-GA algorithm is proposed for solving the elevator group control system optimization problems. This research has an important practical value and a broad application prospect.This main work of this paper is as follows:(1)The relevant information at home and abroad is searched, combined with the elevator group control system technology development and research status, the existing elevator group control algorithm is summarized, the research program of the PSO-GA hybrid algorithm is designed to solve multi-objective optimization problem.(2) The characteristic of elevator group control system is analyzed, including the multi-objective, uncertainty, nonlinear, disturbance and incompleteness, aiming at these characteristics to determine the scheduling principle, the system evaluation indicators and building traffic patterns are also analyzed, the most appropriate group control algorithm should be used in different transport modes to improve the performance of the elevator system.(3) The mathematical model of multi-objective optimization is described, the comprehensive evaluation function which to reduce the weighted average of the waiting time, the average rising time and the energy consumption is proposed. According to different traffic modes to adjust three weighting coefficients, the multi-objective optimization model of the elevator group control system is established.(4) The multi-objective optimization algorithm of the elevator group control system is discussed, combined with the advantages of the particle swarm optimization algorithm and the genetic algorithm, a hybrid algorithm based on PSO and GA is proposed to optimize three control targets including the waiting time, the rising time and the energy consumption.(5) MATLAB is applied to simulate the elevator group control system, the hybrid algorithm is used to simulate in different traffic patterns, and the experimental results are compared with genetic algorithm, the convergence and optimization effect are analyzed to prove the effectiveness of the hybrid algorithm. (6) The study of this paper is summarized, and a prospect to the next research is made.