how to plot optimization figure of ga with fitness value in x-axes and number of iteration in y-axes in matlab

To plot the optimization figure of Genetic Algorithm (GA) with fitness value on the x-axis and the number of iterations on the y-axis in MATLAB, you can follow the steps below:

1. Run your GA optimization algorithm and store the fitness value and iteration number for each iteration in separate arrays or vectors. Let's assume you have stored the fitness values in an array called fitness_values and the iteration numbers in an array called iterations.

2. Use the plot function in MATLAB to create the optimization figure. Specify the fitness values as the x-axis and the iteration numbers as the y-axis.

Here is an example code snippet that demonstrates how to plot the optimization figure:

main.m
fitness_values = [100 90 80 70 60 50];
iterations = [1 2 3 4 5 6];

plot(fitness_values, iterations, 'o-')
xlabel('Fitness Value')
ylabel('Number of Iterations')
title('Optimization Figure of Genetic Algorithm')
grid on
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In the above example, I have assumed that the fitness values are stored in the array [100 90 80 70 60 50] and the iteration numbers in the array [1 2 3 4 5 6]. You can replace these values with your actual data.

The plot function is used to create the scatter plot with markers ('o') connected by lines ('-'). The xlabel, ylabel, and title functions are used to set the labels and title for the figure. The grid on command adds a grid to the figure for better visualization.

You can customize the plot further by changing the marker style, line style, color, etc., using the available options in MATLAB.