Open AccessA Multi-AGV scheduling planning method based on improved GA
Author(s) -
Yi Zhang,
Mengsi Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1550/2/022014
Subject(s) - mathematical optimization , scheduling (production processes) , power consumption , computer science , genetic algorithm , population , power (physics) , mathematics , physics , demography , quantum mechanics , sociology
The path planning of Multi-AGV does not especially consider the power consumption. Therefore, a new Multi-AGV scheduling planning method based on improved GA(Genetic Algorithm) is proposed. The improvement of this algorithm is showed in three aspects: first, in order to ensure that AGVs have the power to perform the task, the operation of power evaluation is added after each iteration is completed; second, the objective function will have two constraints: first, the minimum total power consumption for all AGV; second, the maximum power consumption of a single AGV is minimal; finally, by changing the mutation operator of the GA, the convergence speed and the convergence of the population are improved. The simulation results show that the improved GA scheduling results are more reasonable, and under the same conditions, AGVs power consumption will be smaller.