C++ Simple GA
In this first project you are to write the simple GA using C++. Your problem should use the basic simple GA to evolve a string of all ones. Use the STL bitset to hold the bits of a chromosome. You are to have a population size of 50 chromosomes and each chromosome should be 20 bits long. Your crossover operator should be one point crossover with a probability of pcross(.8) and your mutation operation should randomly flip each bit with a probability of pmut(.o1). Use a roulette proportional selection algorithm. Have the GA stop when the optimal fitness is 20(size of the chromosome) or when 1000 iterations have been completed. New individuals are created using a loop randomly filling each bit with a 0 or 1.
Your program when it stops should print out the optimal chromosome, the iteration it was discovered and the population that it appeared within. Run this problem 10 times using different srand(val) val’s. Change the chromosome size to 40 and do the same. Change the size to 60, 80, 100 and do the same. Write a report explaining what you observe as well as a run output for each chromosome size. Also within the report include a graph of the average fitness for the population from generation 0 to the generation that hit 20.
hi, i have been using cpp for implementing different kinds of algorithm. i love to do these things. let me if you prefer my profile.
5 freelance font une offre moyenne de $28 pour ce travail
I hope to see you in chat. Though I am new to freelancer.com I am an experienced c++ developer with full-stack knowledge and career. I have already have this project developed. I'm sure I can do this perfectly. Than Plus
Hi, I have more than 5 years of experience programming in c, c ++, java and php. I have more than 2 years working as a full-stack programmer. I currently use laravel to manage my web projects in php. I speak S Plus
Hi, I can do what you want in c++. I am M.s student in computer science and I used c++ when we join ACM-ICPC local [login to view URL] in many courses and projects I used genetic algorithm and I know it.