Write down the steps of the genetic algorithm for an optimization problem. If you use any...

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Write down the steps of the genetic algorithm for an optimization problem. If you use any notations, clearly define all of them. (10 marks) You have the below quadratic function and the constraint. You need to write a code to implement the genetic algorithm to find the value that maximize the quadratic function value with respect to the given constraint. f(x) = -0.05x² + 3x + 2; subject to 0 ≤ x < 64 1. Devise a binary chromosome to translate the sample space of candidate solutions to above question. (5marks) 2. Setup the parameters that is required to implement Genetic Algorithm to above question (you may take initial parameter values according to your preference). (5marks) 3. Create the initial population, calculate the fitness of each member of population and calculate sampling probabilities for each member of the population. (5marks) 4. Implement the genetic algorithm (iterate your initial population up to certain number of generation) and derive the solution to above question. Your implementation should include the following. (50 marks) a. Selection of chromosomes to reproduce b. Crossover to produce next generation of chromosomes c. Random mutation of chromosomes in new generation 5. Plot the average fitness and maximum fitness with the generation. (10 marks) 6. Repat the above process for another 2 runs. Check whether all the runs give the same solution. Is it possible to have different solutions in different runs? Explain. (15 marks) Write down the steps of the genetic algorithm for an optimization problem. If you use any notations, clearly define all of them. (10 marks) You have the below quadratic function and the constraint. You need to write a code to implement the genetic algorithm to find the value that maximize the quadratic function value with respect to the given constraint. f(x) = -0.05x² + 3x + 2; subject to 0 ≤ x < 64 1. Devise a binary chromosome to translate the sample space of candidate solutions to above question. (5marks) 2. Setup the parameters that is required to implement Genetic Algorithm to above question (you may take initial parameter values according to your preference). (5marks) 3. Create the initial population, calculate the fitness of each member of population and calculate sampling probabilities for each member of the population. (5marks) 4. Implement the genetic algorithm (iterate your initial population up to certain number of generation) and derive the solution to above question. Your implementation should include the following. (50 marks) a. Selection of chromosomes to reproduce b. Crossover to produce next generation of chromosomes c. Random mutation of chromosomes in new generation 5. Plot the average fitness and maximum fitness with the generation. (10 marks) 6. Repat the above process for another 2 runs. Check whether all the runs give the same solution. Is it possible to have different solutions in different runs? Explain. (15 marks)

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To solve the optimization problem using a genetic algorithm with a quadratic function and the given constraint here are the steps 1 Binary Chromosome Representation Convert the continuous space to a b... View the full answer