Black box optimization using evolutionary algorithm with novel selection and replacement strategies based on similarity between solutions

Result of experiments show how using the proposed strategies increases performance of genetic algorithm in terms of accuracy, on function optimization datasets. In addition, the proposed algorithms in this paper can be easily applied to different types of the population-based evolutionary algorithms. Results of experiments show how the proposed algorithms improve the performance of differential evolutionary algorithm in terms of accuracy, on variety of datasets including CEC-2015 Black Box Optimization.