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Task is to find approximations to optimal solution, graident and hessian that minimizes the function, through steepest decent method. My working so far : function
Task is to find approximations to optimal solution, graident and hessian that minimizes the function, through steepest decent method. My working so far : function SteepestDMethodFinal Initial point x; ; ; Function handle for the objective function f @xx xx xxxxxxx; Gradient of the objective function gradf @xx x; x xx; xx; steepest decent method xopt, fopt, gradopt SteepestDMethodf gradf x; Display results dispApproximated Optimal point:; dispxopt; dispApproximated Function value at optimal point:; dispfopt; dispApproximated Gradient at optimal point:; dispgradopt; end function xopt, fopt, gradopt SteepestDMethodf gradf x Parameters tol e; maxiter ; Initialization x x; g gradfx; d g; k ; while normg tol && k maxiter Line search to find optimal step size alpha alpha fminbnd@a fx ad; Update the point x x alpha d; Compute new gradient gnew gradfx; Update the direction d g; Update the gradient g gnew; Increment iteration counter k k ; end Optimal values xopt x; fopt fxopt; gradopt g; end Question : has my code which uses steepest decent method done approximating the optimal soultion and gradient correctly
Task is to find approximations to optimal solution, graident and hessian that minimizes the function, through steepest decent method.
My working so far :
function SteepestDMethodFinal
Initial point
x; ; ;
Function handle for the objective function
f @xx xx xxxxxxx;
Gradient of the objective function
gradf @xx x;
x xx;
xx;
steepest decent method
xopt, fopt, gradopt SteepestDMethodf gradf x;
Display results
dispApproximated Optimal point:;
dispxopt;
dispApproximated Function value at optimal point:;
dispfopt;
dispApproximated Gradient at optimal point:;
dispgradopt;
end
function xopt, fopt, gradopt SteepestDMethodf gradf x
Parameters
tol e;
maxiter ;
Initialization
x x;
g gradfx;
d g;
k ;
while normg tol && k maxiter
Line search to find optimal step size alpha
alpha fminbnd@a fx ad;
Update the point
x x alpha d;
Compute new gradient
gnew gradfx;
Update the direction
d g;
Update the gradient
g gnew;
Increment iteration counter
k k ;
end
Optimal values
xopt x;
fopt fxopt;
gradopt g;
end
Question : has my code which uses steepest decent method done approximating the optimal soultion and gradient correctly
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