Seagull optimization algorithm combining Cauchy mutation and elite reverse learning

Xingyu Pan; Shipin Yang; Lijuan Li; Tingting Zhao

doi:10.1117/12.2658869

23 November 2022 Seagull optimization algorithm combining Cauchy mutation and elite reverse learning

Xingyu Pan, Shipin Yang, Lijuan Li, Tingting Zhao

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 124541Z (2022) https://doi.org/10.1117/12.2658869
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

In recent years, with the rapid growth of the number of cars, the problem of "difficult parking" has become increasingly prominent, especially in the parking lot. It often takes a long time for drivers to find a free parking space. Low parking efficiency seriously affects the driver's parking feeling, which is an urgent problem to be solved. In view of this phenomenon, based on the analysis of the internal structure of the parking lot, this paper abstractly establishes the parking guidance data model, comprehensively considers the restrictive factors affecting the driver's parking psychology, then uses the improved Dijkstra algorithm to optimize the guidance data model, and finally finds out the optimal parking path, which greatly improves the parking efficiency and parking feeling.

Citation Download Citation

Xingyu Pan, Shipin Yang, Lijuan Li, and Tingting Zhao "Seagull optimization algorithm combining Cauchy mutation and elite reverse learning", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 124541Z (23 November 2022); https://doi.org/10.1117/12.2658869

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