基于柯西迁移烟花算法的仓储群机器人任务分配  

Task Allocation of Warehouse Swarm Robotic Based on Cauchy Migration Fireworks Algorithm

作　　者：薛颂东[1] 梁金琳 XUE Songdong LIANG Jinlin(Software Engineering Institute,Taiyuan University of Science and Technology,Taiyuan 030024)

机构地区：[1]太原科技大学软件工程研究所,太原030024

出　　处：《计算机与数字工程》2024年第8期2510-2517,共8页Computer & Digital Engineering

基　　金：山西省高校科技创新项目(编号:2021L322);山西省高校教学改革创新项目(编号:J2021441);山西省哲社科学规划课题(编号:2020-270)资助。

摘　　要：为提升智能仓储调度中群机器人任务分配的效率,提出一种柯西迁移烟花算法。综合考虑群机器人完成任务的行走距离、耗费时间、任务分配均衡性,构造适应度函数。以机器人电量作为约束条件,将群机器人动态任务分配建模为适应度函数优化的烟花模型,并引入柯西迁移变异火花和基于适应度函数的选择策略。最后,与常用的其他算法进行对比仿真实验。结果表明,柯西迁移烟花算法改善了易陷入局部最优和收敛速度慢的问题,用于群机器人任务分配的效率较其他算法更有优势。To enhance the efficiency of swarm robotic task allocation in intelligent warehousing scheduling,a Cauchy migration fireworks algorithm is proposed.The fitness function is firstly constructed integrating three indices including walking distance,elapsed time and task balance among the member robots as the optimization objective.Considering the robot power as constraint,the dynamic task allocation is then modeled as a basic fireworks algorithm.And then a Cauchy migration mutation spark and a selection strategy based on fitness function are introduced.Finally,Cauchy migration fireworks algorithm is compared with another ones through simulation.The experimental results show that the phenomena of tempted local optimum and slow convergence are improved,and that Cauchy migration fireworks algorithm dominates the above opponents on task allocation efficiency.

关 键 词：智能仓储 群机器人 任务分配 烟花算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]