how to write genetic algorithm code that minimize fitness function with 9 variables as input in matlab

To write a genetic algorithm code in MATLAB that minimizes a fitness function with 9 variables as input, you can follow these steps:

1. Define the fitness function:

   main.m
   function fitness = myFitnessFunction(x)
      % your fitness function logic here
   end
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2. Define the number of variables and their ranges:

   main.m
   numVariables = 9;
   lb = [-10 -10 -10 -10 -10 -10 -10 -10 -10];
   ub = [10 10 10 10 10 10 10 10 10];
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3. Set up the genetic algorithm options:

   main.m
   options = gaoptimset('Display', 'iter', 'PopulationSize', 50);
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4. Run the genetic algorithm optimization:

   main.m
   [xOpt, fOpt] = ga(@myFitnessFunction, numVariables, [], [], [], [], lb, ub, [], options);
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   Here, xOpt is the optimal solution (an array of 9 variables) and fOpt is the corresponding fitness value.

5. Display the results:

   main.m
   fprintf('Optimal solution: %s\n', num2str(xOpt));
   fprintf('Optimal fitness value: %f\n', fOpt);
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You can modify the fitness function and other parameters according to your specific problem requirements.