Week 5 - Genetic Algorithm

Report on Genetic Algorithm

Aim:

• To optimise the stalagmite function and find the global maxima of the function.

Software Used: MATLAB.

Code:

Stalagmite Code:

Explanation:

• Defines x and y values ranging from 0 to 0.6 with 150 points each.
• Uses meshgrid(x, y) to create a 2D coordinate matrix for function evaluation.
• Iterates through each (x, y) pair, evaluating the stalagmite function at those points.
• Uses surfc(xx, yy, -f) to visualize the stalagmite function in 3D.
• Runs ga() 50 times without constraints to find a global maximum.
• Genetic Algorithm (GA) is an optimization technique inspired by natural selection and evolution. It is used to find the best solution to a problem by mimicking the process of survival of the fittest.
• Marks optimized values on the function’s surface plot using red markers.
• GA Adds search constraints (0 ≤ x, y ≤ 0.6) for a more realistic search space.
• Plots optimized points from the constrained GA search.
• Executes GA 50 times with modified population size and bounded constraints.
• Plots function maximum values vs. iterations to observe GA performance.
• Uses tic and toc to measure the computation time for each optimization case.

Result:

Conclusion:

• The stalagmite function and the global maxima of the function is optimised .