The Scheduling Of Multi-objective Elevator Group Control Algorithm Based On Pso

With the development of society, elevator, as the vertical transporting facility is more and more widely used with the emergence of intelligent buildings. The quality of elevator services needs to be improved to satisfy the passengers'requirements. Single elevator is insufficient for the inner building transportation. Multi- elevator service could shorten the waiting time and reduce energy consuming. As a consequence, the Elevator Group Control System (EGCS) is introduced. The EGCS improves the service efficiency and quality by an optimized control policy, which harmonizes multi- elevator operation. As the elevator group control system of the control objectives diversity inherent in random and non-linear, so it is more difficult to solve a multi-objective optimization problem.This thesis analyzes and studies the characteristic and performance evaluation indicators of the system and the traffic patterns of buildings, summarizes the existent elevator group control algorithm. Based on this, to reduce the average waiting time and taking time, as well as the energy consumption is three important objectives, we take the weighted average of the three objectives as the elevator dispatching comprehensive evaluation function, and adjust the weighting coefficients based on different traffic patterns. Study of particle swarm optimization (PSO) and multi-objective particle swarm optimization algorithm, PSO algorithm as a framework, designed to meet the fitness function as the core, the multi-objective particle swarm optimization applied to the EGCS. Using the PSO to achieve three specific control objectives and dispatch the multi-elevator under different traffic patterns. In the Windows 2000/XP environment, using Visual Basic6 language preparation of elevator group control system dynamic performance analysis software, construction of the EGCS development structure. It provides a convenient test platform to evaluate the group control algorithms, simulate elevator operation process and configure the elevators.Finally, using the development structure to simulate the group control algorithm, the results show that, the system performance can be greatly improved through using the most suitable arithmetic in different traffic mode. Compared with the traditional group control algorithm, the average waiting time and taking time, as well as the energy consumption has been decreased, improve the efficiency of the system optimization, and increase of passenger satisfaction, to achieve the purpose of the system energy.