In MATLAB

Explicitly program a function SA.m that finds the global minimum of a function f using Simulated Annealing. Use the SA pseudocode as your guide. The program SA.m has the following format: SA(f, dim, domain, start, TO, Lambda, minTemp) f is the handle of the function to be optimized dim is the number of input arguments to f domain is a (1 times 2)-array that tells the program the domain of each input argument (e.g. [-500, 500]). start is a (dim x 1)-array (dim-vector) that specifies the start values for all dim input arguments for the SA algorithm T0 is the initial temperature Lambda is the cooling rate minTemp is the temperature at which the SA algorithm quits. Your program should return the minimum found. Explicitly program a function SA.m that finds the global minimum of a function f using Simulated Annealing. Use the SA pseudocode as your guide. The program SA.m has the following format: SA(f, dim, domain, start, TO, Lambda, minTemp) f is the handle of the function to be optimized dim is the number of input arguments to f domain is a (1 times 2)-array that tells the program the domain of each input argument (e.g. [-500, 500]). start is a (dim x 1)-array (dim-vector) that specifies the start values for all dim input arguments for the SA algorithm T0 is the initial temperature Lambda is the cooling rate minTemp is the temperature at which the SA algorithm quits. Your program should return the minimum found