Research on path planning problem based on improved genetic algorithm

Guangya Zhang

doi:10.1117/12.3004169

11 October 2023 Research on path planning problem based on improved genetic algorithm

Guangya Zhang

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128000X (2023) https://doi.org/10.1117/12.3004169
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Due to the low local optimization accuracy, long search time, and susceptibility to local optima in traditional genetic algorithms, their applications in path planning and other aspects are not very widespread. Therefore, this paper proposes a new improved genetic algorithm, which improves the crossover mutation operator on the basis of traditional genetic algorithms, making the algorithm effectively avoid falling into local optima problems and has stronger search ability, simultaneously incorporating the idea of simulated annealing to obtain a new population, it has stronger adaptability and global optimization ability. The experimental results of simulation research on the improved genetic algorithm show that the algorithm has relatively good superiority and feasibility.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guangya Zhang "Research on path planning problem based on improved genetic algorithm", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128000X (11 October 2023); https://doi.org/10.1117/12.3004169

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