The implementation of crossover factor, fTIG in the Finite Persisting Sphere Genetic Algorithm

In this paper, a crossover factor, fTIG is introduced to the Finite Persisting Sphere Genetic Algorithm (FPSGA). The factor provides a variable range of the loop in the process of Finite Persisting Sphere. By the existing of the variable range, the risk to have too large number of loop or too small number of loop in the FPSGA can be reduced. Too large number of loop will risk of repeating using the same data and too small number of loop will cause the loss of good genes in the FPSGA. By the proposed approach, potential to achieve the global solution in a small number of population will be increased and at the same time less time required running the process in the loop. This paper show that FPSGA with fTIG has higher global solution compared to other method and this method has faster converges to the global solution. The experiment result revealed the superiority of fTIG in FPSGA.