About this document
Hybrid MGO-GA for Growth Optimization by IJMSRT is a document available to read on EtoBox.
The document presents a study on a hybrid optimization approach called MGO-GA, which combines Moss Growth Optimization (MGO) with Genetic Algorithm (GA) to enhance optimization performance. The results demonstrate that MGO-GA outperforms the standard MGO algorithm in 14 out of 23 benchmark functions, improving accuracy, stability, and convergence speed. The proposed method effectively addresses the limitations of MGO, such as premature convergence and stagnation, by incorporating genetic operators to enhanc
- Author
- IJMSRT
- Language
- EN