基于免疫蚁群优化算法的仓储任务调度  

Warehouse Task Scheduling Based on Immune Ant Colony Optimization Algorithm

作　　者：杨桂华[1] 卫嘉乐 YANG Gui-hua;WEI Jia-le(College of Mechanical and Control Engineering,Guilin University of Technology,Guilin 541004,China)

机构地区：[1]桂林理工大学机械与控制工程学院,桂林541004

出　　处：《组合机床与自动化加工技术》2023年第1期179-183,共5页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金地区基金项目(52065016);广西研究生教育创新计划项目(JGY2021091)。

摘　　要：针对仓储机器人群的多目标任务分配问题,以最小距离成本为目标,建立了仓储机器人群调度方案的数学模型。以免疫算法为基础,提出了一种免疫蚁群优化算法。通过融合、改进免疫算法和蚁群算法,弥补了免疫算法因冗余信息多导致的迭代时间长、收敛速度慢以及蚁群算法初期信息素积累时间较长,速度慢的缺陷,提高了算法的效率。再多次进行对比实验,从算法运行时间,机器人群的距离成本角度验证了改进算法的可行性。Aiming at the multi-objective task assignment problem of warehouse robot crowd,a mathematical model of warehouse robot crowd scheduling scheme was established with the goal of minimum distance cost.Based on immune algorithm,an immune ant colony optimization algorithm was proposed.Through fusion and improvement of immune algorithm and ant colony algorithm,the defects of immune algorithm due to redundant information,such as long iteration time and slow convergence,and ant colony algorithm,such as long pheromone accumulation time and slow speed,were made up,and the efficiency of the algorithm was improved.The feasibility of the improved algorithm is verified from the running time of the algorithm and the distance cost of the robot population by several comparative experiments.

关 键 词：仓储机器人 多目标调度 免疫优化算法 

分 类 号：TH165[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]