基于改进遗传算法的智能存储多agv调度研究

2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA) Pub Date : 2023-03-01 DOI:10.1109/PRMVIA58252.2023.00041

Haowen Sun, Liming Zhao

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引用次数: 0

摘要

智能仓储已经成为各个物流行业的重要组成部分，多移动机器人的任务分配是智能仓储的重要组成部分。本文以机器人运输成本和空载作业成本、任务完成时间成本和任务分配平衡为优化目标。针对多移动机器人任务分配的优化问题，提出了一种改进的遗传算法。通过建立数学模型;采用自适应调整交叉概率和改进遗传算法的适应度函数来提高种群的收敛速度和收敛性。实例仿真表明，改进后的遗传算法收敛速度更快，分配效果更好。

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Research on multi-AGV scheduling for intelligent storage based on improved genetic algorithm

Intelligent storage has become an important part of various logistics industries, and task assignment of multi-mobile robots is an important part of intelligent storage. In this paper, the robot transport cost and no-load operation cost and task completion time cost and task assignment balance are used as optimization objectives. An improved genetic algorithm is proposed for the optimization of task assignment of multi-mobile robots. By establishing a mathematical model; adaptively adjusting the crossover probability and the fitness function of the improved genetic algorithm are used to improve the convergence speed and convergence of the population. Example simulations show that the improved genetic algorithm converges faster and has a better assignment.

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2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA)

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