@article{Jalal-ud-Din2024, 
author = { Jalal-ud-Din and  Ehtasham-ul-Haq and Ibrahim M. Almanjahie and Ishfaq Ahmad},
title = {Enhancing probabilistic based real-coded crossover genetic algorithms with authentication of VIKOR multi-criteria optimization method},
year = {2024},
journal = {AIMS Mathematics},
volume = {9},
number = {10},
pages = {29250-29268},
keywords = {genetic algorithms, Gumbel crossover, Rayleigh crossover, global optimization, real-coded crossover operator, VIKOR method},
url = {https://www.sciopen.com/article/10.3934/math.20241418},
doi = {10.3934/math.20241418},
abstract = {To improve the performance of genetic algorithms (GAs) in complex optimization settings, this work offered two novel real-coded crossover operators: one based on the Gumbel distribution (GX) and the other on the Rayleigh distribution (RX). These innovative operators, when combined with three different mutation techniques, created a significant improvement in GA methodology. Our meticulous simulations showed that the GX operator significantly outperformed RX and other traditional operators, demonstrating its superior capacity to address complex optimization problems. The GX operator's unusual robustness was further validated through detailed performance analysis utilizing the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) multi-criteria decision-making technique, setting a new standard in crossover operator design and significantly improving the state of the art in GAs.}
}