Implement a simple GA with fitness-proportionate selection, roulette-wheel sampling, population…

TASK
a) Implement a simple GA with fitness-proportionate selection, roulette-wheel
sampling, population size100, single-point crossover rate pc = 0.7, and bitwise
mutation rate pm = 0.001. The used chromosome representation is the 64-bit IEEE-754
double precision format.
b) The fitness function is designed to estimate the root of the function:
??(??) =
??
10 ?17 –
200
??
?
??
?
? + 21
Consider the search range is within [-100, 100].
2. Result Analysis
TASK
a) Report results of five runs. Every result set is obtained by running the GA for 100
generations and plotting the fitness of the best individual found at each
generation as well as the average fitness of the population at each generation.
b) Discuss the convergence consistency of GA to a correct root.