Zebra optimization algorithm developed with FDB-based guidance mechanism for optimum AVR-LFC system design

In this thesis, a zebra optimization algorithm (ZOA) for solving engineering problems presented. The proposed algorithm uses a selection method called Fitness-Distance Balance (FDB). This developed FDB-ZOA algorithm is tested and validated on the CEC17 and CEC20 benchmark problems for search spaces of three different dimensions. The results the FDB-ZOA algorithm are compared with 11 current and powerful algorithms, including the ZOA algorithm. According to the Friedman test results, the FDB-ZOA algorithm ranked first, while the original ZOA algorithm ranked tenth. This shows that the FDB selection method improves the performance of the algorithm. Furthermore, the developed algorithm is used to solve the engineering problem of combined automatic voltage regulator (AVR) and load frequency control (LFC). The obtained results show that the developed algorithm is effective in solving such engineering problems.