A genetic algorithm rooted in integer encoding and fuzzy controller
Mohammad Jalali Varnamkhasti · IAES International Journal of Robotics and Automation (IJRA) · 2019
The premature convergence is the essential problem in genetic algorithms and it is strongly related to the loss of genetic diversity of the population. In this study, a new sexual selection mechanism which utilizing mate chromosome during selection proposed and then technique focuses on selecting and controlling the genetic operators by applying the fuzzy logic controller. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving benchmark problems published in the literature.