TY - JFULL AU - Mahmoud R. Shaghaghian PY - 2010/3/ TI - Fractal Dimension: An Index to Quantify Parameters in Genetic Algorithms T2 - International Journal of Computer and Information Engineering SP - 294 EP - 297 VL - 4 SN - 1307-6892 UR - https://publications.waset.org/pdf/6312 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 38, 2010 N2 - Genetic Algorithms (GAs) are direct searching methods which require little information from design space. This characteristic beside robustness of these algorithms makes them to be very popular in recent decades. On the other hand, while this method is employed, there is no guarantee to achieve optimum results. This obliged designer to run such algorithms more than one time to achieve more reliable results. There are many attempts to modify the algorithms to make them more efficient. In this paper, by application of fractal dimension (particularly, Box Counting Method), the complexity of design space are established for determination of mutation and crossover probabilities (Pm and Pc). This methodology is followed by a numerical example for more clarification. It is concluded that this modification will improve efficiency of GAs and make them to bring about more reliable results especially for design space with higher fractal dimensions. ER -