Title
A Q-learning based multi-strategy integrated artificial bee colony algorithm with application in unmanned vehicle path planning
Author
Ni, Xinrui (Beijing Jiaotong University)
Hu, Wei (Beijing Jiaotong University)
Fan, Q. (TU Delft Discrete Mathematics and Optimization)
Cui, Yibing (Beijing Jiaotong University)
Qi, Chongkai (Beijing Jiaotong University)
Date
2024
Abstract
Artificial bee colony (ABC) is a prominent algorithm that offers great exploration capabilities among various meta-heuristic algorithms. However, its monotonous and one-dimensional search strategy limits its searching performance in the solving process. Thus, to address this issue, a Q-learning based multi-strategy integrated ABC algorithm (QMABC) is proposed. In the QMABC, multiple search strategies are proposed to utilize different individual experiences and search approaches for solution updates. Then, Q-learning is employed for strategy selection. In comparison to previous studies, this paper introduces more effective state and action configurations within the framework of Q-learning. To evaluate the performance of the QMABC, CEC 2017 benchmark functions are adopted to compare it to different meta-heuristic algorithms including ABC based and non-ABC based algorithms. Moreover, applications in path planning are implemented to further verify the effectiveness of the QMABC. Overall, it should be highlighted that the proposed QMABC demonstrates superiority in both numerical and practical experiments.
Subject
Artificial bee colony algorithm
Meta-heuristic algorithm
Multi-strategy
Path planning
Q-learning framework
To reference this document use:
https://doi.org/10.4233/uuid:69402ff3-ea24-40bb-a99e-633ee1901351
DOI
https://doi.org/10.1016/j.eswa.2023.121303
Embargo date
2024-03-25
ISSN
0957-4174
Source
Expert Systems with Applications, 236
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2024 Xinrui Ni, Wei Hu, Q. Fan, Yibing Cui, Chongkai Qi