Improving Zebra Optimization Algorithm via Fitness-Distance Balance Strategy: Application to AVR-LFC System
OPTIMAL CONTROL APPLICATIONS & METHODS, vol.46, no.6, pp.2771-2798, 2025 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 46 Issue: 6
- Publication Date: 2025
- Doi Number: 10.1002/oca.70028
- Journal Name: OPTIMAL CONTROL APPLICATIONS & METHODS
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
- Page Numbers: pp.2771-2798
- Keywords: AVR-LFC system control, fitness-distance balance, performance improvement of metaheuristic search algorithms, zebra optimization algorithm
- Karadeniz Technical University Affiliated: Yes
Abstract
This study proposes the FDB-ZOA algorithm, which is an improved version of the Zebra Optimization Algorithm (ZOA) with the Fitness-Distance Balance (FDB) strategy to enhance the exploration and exploitation balance. The developed algorithm was tested on CEC2020 benchmark functions and compared with 13 different state-of-the-art meta-heuristic algorithms, including ZOA. The comparisons were supported by mean success, standard deviation, box plots, convergence curves, and Wilcoxon and Friedman tests; FDB-ZOA demonstrated superior performance in all dimensions. Additionally, the algorithm's application potential has been demonstrated through parameter optimization of FOPID and FOPI-FOPD controllers in AVR-LFC systems, with results validated via time domain analysis, robustness tests, and OPAL-RT-based real-time simulations. The findings obtained indicate that FDB-ZOA is a strong candidate solution from both theoretical and practical perspectives.