This Program will find the Minimum Value of some Dataset, using Genetic Algorithm Method to find the minimum value of the Formula
The Data is consist of some randomly generated binary encoding with a total length of 32 element/bit for each of its chromosomes
to decode the chromosome of the binary type, I applied the following formula and broke it down into Some parts in a Bgst() function to determine the x1, x2 phenotype of a chromosomes which will later become parameters for other functions
I calculated the Fitness of a chromosome after getting the x1, x2 phenotype of a chromosome
The crossover was carried out after the selection of two parent candidates that I chose based on fitness scores best in its generation, the probability of occurrence of crossovers that I use is 70% with the single-point method is set to be in the middle of the total length of a chromosome ie index to 16. The elements are cut into the front and back, then combined so that L produces new chromosomal offspring. If the probability is not met, the first parent will be copied to become the new chromosome child.
The generational replacement method that I use is generational replacement in each generation Elitism is carried out where the two chromosomes with the highest fitness value are ensured to be in the generation Furthermore, the crossover & mutation results from the selected parent will fulfill the generational pool I save it in an array variable. The alternation of generations will occur at the end of the iteration indicated by The old population will be replaced by a new population containing elite chromosomes and children from the parent the chosen.
Evolution was stopped after the maximum generation limit was reached, I applied this method so that termination of evolution can be arranged easily by only changing the value of one variable
