摘要
Abstract
Considering the task assignment,path planning,and deadlock challenges inherent in 2D shuttle systems,a hybrid scheduling strategy based on an improved genetic algorithm(GA)and dynamic priority rules was proposed.By establishing a mathematical model to analyze operational constraints,a genetic algorithm with adaptive crossover and mutation operators was developed to optimize task assignment,and a dynamic conflict detection mechanism was integrated to achieve collaborative path optimization for multiple shuttles.Simulation results demonstrate that,compared with the traditional FIFO algorithm,this method reduces job completion time by 18.7%and increases system throughput by 22.3%under a scenario comprising 1000 access tasks,providing an effective solution for shuttle scheduling in high-density warehousing environments.关键词
二向穿梭车/智能仓储/任务调度/遗传算法/路径规划Key words
2D shuttle/intelligent warehousing/task scheduling/genetic algorithm/path planning分类
信息技术与安全科学
