摘要
多AGV调度系统作为仓储物流系统的核心,为了提高AGV协同完成任务的效率,提出一种基于文化算法框架的改进遗传算法。改进的遗传算法采用将AGV调度和任务分配分别编码并进行交叉遗传操作,实现任务调度和路径规划同步进行。然后将改进后的算法融入文化算法框架,种群空间按照改进遗传算法进行进化,并将进化后的较优个体提供给信念空间,信念空间提取其中更优的个体并利用知识进行更新进化。最后对比改进遗传算法和文化混合算法对模型求解的优劣性,通过算例结果表明,文化混合算法得到的调度结果在完成任务时间和运行速度上更优。
Multi⁃AGV dispatching system is the core of warehousing and logistics system.An improved genetic algorithm based on the framework of cultural algorithm is proposed to improve the collaborative operation efficiency of AGVs.In the im⁃proved genetic algorithm,AGV scheduling and task allocation are encoded separately for cross genetic operation,so as to realize the synchronization of task scheduling and path planning.And then,the improved algorithm is integrated into the framework of the cultural algorithm.The population space is evolved according to the improved genetic algorithm.The better individuals after evolution are provided for the belief space.The much better individuals are extracted in the belief space,and updated and evolved with knowledge.Finally,the improved genetic algorithm and cultural hybrid algorithm are compared in the aspects of the advantages and disadvantages of model solving.The calculating results of examples show that the scheduling results obtained by cultural hybrid algorithm are better in terms of the duration of task completion and the running speed.
作者
曾亮
詹逸鹏
王粟
ZENG Liang;ZHAN Yipeng;WANG Su(Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System,Hubei University of Technology,Wuhan 430068,China;.Research Center of Hubei Power Grid Intelligent Control and Equipment Engineering Technology,Hubei University of Technology,Wuhan 430068,China)
出处
《现代电子技术》
2021年第9期105-109,共5页
Modern Electronics Technique
基金
国家自然科学基金资助项目(51977061)
国家自然科学基金资助项目(61903129)。
关键词
AGV调度
仓储物流
文化混合算法
任务分配
路径规划
冲突规避
AGV scheduling
warehouse logistics
cultural hybrid algorithm
task allocation
path planning
conflict avoidance
