Implement the genetic algorithm (GA):
Maximize f(X1, X2, X3) = (X1)^2 + (X2)^2 + (X3)^2, for -1.0 <= Xi <= 1.0, i = 1, 2, 3.
That is, the goal is to find values of X1, X2, and X3 (in the given interval) that will cause f(.,.,.) to have the maximum value. Use real (floating-point) values, not bit-string representations. Use proportional selection, single-point crossover, and gene-wise mutation.
Use the following parameter values:
N = 20; pc = 0.6 to 1.0; pm = 0.05 to 0.3; max generations (for use as a stopping condition) = 50.
For each of three “typical” single runs, report the following:
At intervals of 10 generations, the best and the worst fitnesses in the current generation and the corresponding X-vectors; the average fitness of all the members of the current generation; the best-of-run solution (the vector and its fitness).
Next, collect data on 30 independent runs, and then report, at intervals of 10 generations, the following averages (and the corresponding standard deviations) over 30 items: the best-of-generation fitness, the average-of-generation fitness, the best-of-run fitness. That is, these three quantities are each an average of 30 values.
Hi,
I have good experience in GA development and i reviewed your requirement it's looking good to me.I worked on few assignment in which i developed GA algo, apart from that i know the java library for genetic algorithm. your job description is looking fine for me and i would like to discuss further with you, Please feel free to message me when you have time.
Thanks,
Hello,
I am interested in your project, and ready to provide it.
I am very experienced in assignments like this one, please check my reviews for an idea of my past work.
I will need the lecture notes, so I don't use techniques not covered.
Please note that I ask for milestone payments (escrow) to be setup before starting work.
Regards
Khaled
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