Consider the following problem min f(x)=x1+x2 T2 Suppose that the logarithmic barrier method is used to...
(45 Points) Consider the constrained optimization problem: min f(x1, x2) = 2x} + 9x2 + 9x2 - 6x1x2 – 18x1 X1 X2 Subject to 4x1 – 3x2 s 20 X1 + 2x2 < 10 -X1 < 0, - x2 < 0 a) Is this problem convex? Justify your answer. (5 Points) b) Form the Lagrange function. (5 Points) c) Formulate KKT conditions. (10 Points) d) Recall that one technique for finding roots of KKT condition is to check all permutations...
2. Consider the following function: f (x1, x2) = x1 – 2V82 (a) Write down the Hessian matrix. (b) Is the function convex at the point (x1 = 1, X2 = 2)?
Problem 1: A firm has the following production function: min{x1, 2x2) f(x,x2)= A) Does this firm's technology exhibit constant, increasing, or decreasing returns to scale? B) What is the optimality condition that determines the firm's optimal level of inputs? C) Suppose the firm wants to produce exactly y units and that input 1 costs $w per unit and input 2 costs $w2 per unit. What are the firm's conditional input demand functions? D) Using the information from part D), write...
x1.x2 Subject to 4x1-3x2 S 20 x1 +2x2 s 10 a) Is this problem convex? Justify your answer. (5 Points) b) Form the Lagrangian function. (5 Points) c) Formulate KKT conditions. (10 Points) d) Recall that one technique for finding roots of KKT condition is to check all permutations of the switching conditions. Find an optimal solution (x*) via e) Compute the objective function and identify each constraint as active or f) Solve this problem using graphical optimization to check...
Solve the following problem using Lagrange multiplier method: Maximize f(x,y,z) = 4y-2z subject to the constraints 2x-y-z 2 x2+y2- 1 1. (1) (2) (Note: You need not check the Hessian matrix, just find the maximum by evaluating the values of f(x,y,z) at the potential solution points) Also, using sensitivity analysis, find the change in the maximum value of the function, f, if the above constraints are changed to: (3) (4) 2x -0.9y-z 2 x2+ y2- 0.9. Solve the following problem...
Solve the following problem using Lagrange multiplier method: Maximize f(x,y,z) = 4y-2z subject to the constraints 2x-y-z 2 x2+ y2- 1 (1) (2) (Note: You need not check the Hessian matrix, just find the maximum by evaluating the values of f(x,y,z) at the potential solution points) Also, using sensitivity analysis, find the change in the maximum value of the function, f, if the above constraints are changed to: (3) (4) 2x-0.9y-z =2 x2+y2- 0.9 Solve the following problem using Lagrange...
Problem 5. Consider the dynamics of two mass mechanical system captured by d2xi(t) Middt?t2+k(x1(t)-x2(t)) = f(t) d'x2(t) dt2 + k(x2(t)-x where M, , M2, and k are constants. Suppose the input is () and the output is X2 (t), find the transfer function G(s) of the system. Note: Consider all zero initial conditions.
Consider the following LP problem. MAX: 9X1-8X2 Subject to: x1+x2≤6 -x1+x2≤3 3x1-6x2≤4 x1,x2≥0 Sketch the feasible region for this model. What is the optimal solution? What is the optimal solution if the objective function changes to Max.-9x1+8x2?
please answer step by step Solve the following problem using Lagrange multiplier method: Maximize f(x.y,z) = 4y-2z subject to the constraints 2x-y-z 2 x2+ y2-1 1. (1) (2) (Note: You need not check the Hessian matrix, just find the maximum by evaluating the values of f(x,y,z) at the potential solution points) Also, using sensitivity analysis, find the change in the maximum value of the function, f, if the above changed to: (3) (4) constraints are 2x-0.9y-z 2 x2+y2-0.9. Solve the...
Theoretical Part 1. Consider the problem of computing f(x)dx, where f(x) could be any function. Letting X1, X2 IID ~U[0, 2, define three very simple estimators: ff(0)f(2), i2= f(X1)f(X2), fi3 = f(X1/2) + f((X2+2)/2) (a) (5 points) Is ft an unbiased estimator of u? (b) (5 points) Is i2 an unbiased estimator of ? (c) (5 points) Is 3 an unbiased estimator of ? (d) (10 points) Compute the variance of each of the three estimator when f(x) x Theoretical...