Question: EXERCISE: KKT CONDITIONS AND PENALTY FUNCTION METHOD Consider the NLP problem below, Minimizef(x)=10x12+2.5x225x1x21.5x1+10Subjecttog1(x)=3x122x222x15g1(x)=2(x12)22x241x1,x28 (i) Plot the functions contours along with constraints. (ii) Determine the Jacobian

EXERCISE: KKT CONDITIONS AND PENALTY FUNCTION METHOD Consider the NLP problem

EXERCISE: KKT CONDITIONS AND PENALTY FUNCTION METHOD Consider the NLP problem below, Minimizef(x)=10x12+2.5x225x1x21.5x1+10Subjecttog1(x)=3x122x222x15g1(x)=2(x12)22x241x1,x28 (i) Plot the functions contours along with constraints. (ii) Determine the Jacobian Matrix and Hessian Matrix. (iii) Check whether the points of (2,1)T and (1,4)T is Kuhn Tucker points. (iv) Write the pseudo-objective function for the optimization problem above. Use the bracket penalty term. (v) Solve the question (iv) above using the Matlab's built-in function, i.e., fminsearch. Starting at x(0)=(2,4)T and show the computation in detail

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