Title : 
A Further Improvement on a Genetic Algorithm
         
        
            Author : 
Stewart, Ian ; Feng, Wenying ; Akl, Selim
         
        
        
        
        
        
            Abstract : 
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.
         
        
            Keywords : 
genetic algorithms; probability; acceptance probability parameter; benchmark functions; genetic algorithm; human interaction; Genetic algorithms; Benchmark Function; Crossover; Fitness Function; Genetic Algorithm; Mutation;
         
        
        
        
            Conference_Titel : 
Information Technology: New Generations, 2009. ITNG '09. Sixth International Conference on
         
        
            Conference_Location : 
Las Vegas, NV
         
        
            Print_ISBN : 
978-1-4244-3770-2
         
        
            Electronic_ISBN : 
978-0-7695-3596-8
         
        
        
            DOI : 
10.1109/ITNG.2009.240