An ant colony path planning optimization based on opposition-based learning for AUV in irregular regions
Authors:
- 16 May 2024
- journal article
- research article
- Published by Springer Nature in Computing
- Vol. 106 (7) , 2489-2520
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (62171179)
This publication has 38 references indexed in Scilit:
- ACO+PSO+A*: A bi-layer hybrid algorithm for multi-task path planning of an AUVComputers & Industrial Engineering, 2022
- Novel enhanced Salp Swarm Algorithms using opposition-based learning schemes for global optimization problemsExpert Systems with Applications, 2022
- A dual opposition-based learning for differential evolution with protective mechanism for engineering optimization problemsApplied Soft Computing, 2021
- 2D multi-area coverage path planning using L-SHADE in simulated ocean surveyApplied Soft Computing, 2021
- A differential moth flame optimization algorithm for mobile sink trajectoryPeer-to-Peer Networking and Applications, 2020
- Data collection from underwater acoustic sensor networks based on optimization algorithmsComputing, 2019
- Success history applied to expert system for underwater glider path planning using differential evolutionExpert Systems with Applications, 2019
- Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithmExpert Systems with Applications, 2019
- Generalized Ant Colony Optimizer: swarm-based meta-heuristic algorithm for cloud services executionComputing, 2018
- Route planning evaluation of a prototype optimised infield route planner for neutral material flow agricultural operationsBiosystems Engineering, 2017