A Further Improvement on a Genetic Algorithm
Ian James Stewart, Wenying Feng, Selim G. Akl · 2009
In this paper, a new genetic algorithm is developed based on a pre-existing implementation. The new algorithm requires less human interaction through the use of dynamically selected weight and acceptance probability parameters. The algorithm is implemented and tested using six benchmark functions. Results show that the new algorithm significantly outperforms other genetic algorithms in less time and with less human interaction.