关键词: 立体车库调度优化, 改进混合粒子群算法, 遗传算法, 模拟退火算法

Abstract: To further improve the stereo garage access efficiency, the improved hybrid particle swarm optimization is proposed, which is applied to optimize the stereo garage access period and sequencing. The main purpose of algorithm is to introduce the genetic algorithm in the early stage of the particle swarm optimization algorithm to improve the algorithm’s global search capability, the late introduction of the simulated annealing algorithm to make up for the weakness of the local search ability of the algorithm. Compared with current genetic algorithm, the improved hybrid particle swarm optimization has shown an improved efficiency of 24.5%~36.07% in the stereo garage access, the calculation results also demonstrate that the improved hybrid particle swarm optimization is superior than other scheduling algorithms in the stereo garage operation efficiency.

Key words: stereo garage scheduling optimization, improved hybrid particle swarm optimization, genetic algorithm, annealing algorithm