Problem 1: Consider the following linear optimization problem: max 1 +22x;3 subject to x1 + x2...
Problem 1: Consider the following linear optimization problem: max +22 +rs subject to X1 + X2 + X3 = 10 2x1 - 22 24 i 20, 1,2,3. (a) Bring the problem to a standard form. (b) Show that the point (2,8,0)Ts optimal by the optimality condition of the linear program- ming. Is it an extreme point? Provide arguments for your answers. (c) Determine at least one other point different than (2,8,0)T, which is an extreme point of the constraint set...
Consider the following linear programming model: Max X1 + X2 Subject to: X1 + X2 ≤ 2 X1 ≥ 1 X2 ≥ 3 X1, X2 ≥ 0 This linear programming model has a(n). A. Unbound solution B. Infeasible solution C. Redundant constraint D. Alternate optimal solution
Consider the following linear programming model Max 2X1 + 3X2 Subject to: X1 + X2 X1 ≥ 2 X1, X2 ≥ 0 This linear programming model has: A. Infeasible solution B. Unique solution C. Unbounded Solution D. Alternate optimal solution E. Redundant constraints
8.(15 POINTS) Consider the following optimization problem: Max xi + subject to : 5xí +60192 + 5x3 = 1 and 21 > 0,22 > 0. where 2 and 32 are choice variables. (a) Write the Lagrangean and the Kuhn-Tucker conditions. (6) State and verify the second order condition. Distinguish between sufficient and necessary condi tions. (c) Is the constraint qualification condition satisfied? Show clearly why or why not. (d) Solve the Kuhn-Tucker conditions for the optimal choice: x1, x, and...
Consider the following Linear Problem Minimize 2x1 + 2x2 equation (1) subject to: x1 + x2 >= 6 equation (2) x1 - 2x2 >= -18 equation (3) x1>= 0 equation (4) x2 >= 0 equation (5) 13. What is the feasible region for Constraint number 1, Please consider the Non-negativity constraints. 14. What is the feasible region for Constraint number 2, Please consider the Non-negativity constraints. 15. Illustrate (draw) contraint 1 and 2 in a same graph and find interception...
Consider the following linear program: Max Z = X1 – 2X2 Subject to – 4X1 + 3X2 <= 3 X1 – X2 <= 3 X1, X2 >= 0 a) Graph the feasible region for the problem. b) Is the feasible region unbounded? Explain. c) Find the optimal solution. d) Does an unbounded feasible region imply that the optimal solution to the linear program will be unbounded?
Problem 3. Solve the following LP by the simplex method. max -x1 + x2 + 2xz s. t x1 + 2x2 – x3 = 20 -2x1 + 4x2 + 2x3 = 60 2xy + 3x2 + x3 = 50 X1, X2, X3 > 0 You can start from any extreme point (or BFS) that you like. Indicate the initial extreme point (or BFS) at which you start in the beginning of your answer. (30 points)
Problem 1: Consider the following problem x+y+1=1 x2 +y2+z2 =1 max f(x ,y,z)=er+y+1 subject to (a) Solve the problem. (b) Replace the constraints byx+y+1=1.02 and x2+y2+Z2-0.98. What is the approximate change in the optimal value of the objective function? (c) Classify the candidate points for optimality in the local optimization problem.
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?
(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...