Permuting Convergence Overcomingof Genetic Algorithm Using Arnold Cat Map
Abstract: Today the evolutionary algorithms (EA) such as Genetic algorithm (GA) are used to solve nonlinear optimization problems and find optimum solution. The fundamental of GA is the random where many processes used randomness in their operating. However, the most important disadvantages in GA are permuting convergence which is known to increase the number of iteration for reaching a global optimum. This paper use Arnold Cat Map (ACM) to improve the performance of the GA and to overcome this shortcoming. The experimental results show that the proposed method improves the ability of GA for reaching optimal/near optimal solutions with less number of iterations and significantly improves the solutions quality of the basic GA.
Keywords: Genetic Algorithm, Arnold Cat Map, Crossover, Optimization
How to Cite?: Ruwaida Mohammed Yas, "Permuting Convergence Overcomingof Genetic Algorithm Using Arnold Cat Map", Volume 6 Issue 5, May 2017, International Journal of Science and Research (IJSR), Pages: 2588-2590, https://www.ijsr.net/getabstract.php?paperid=ART20173825, DOI: https://dx.doi.org/10.21275/ART20173825