Solve the LP problem. If no optimal solution exists, indicate whether the feasible region is empty or the objective function is unbounded. HINT [See Example 1.] (Enter EMPTY if the region is empty. Enter UNBOUNDED if the function is unbounded.)
a)Maximize p = 3x + 2y subject to
−4x+y≥10
x+3y≤12
x ≥ 0, y ≥ 0
p=
(x,y)=
b) Maximize and minimize p = x + 2y subject to
x | + | y | ≥ | 6 |
x | + | y | ≤ | 8 |
x | − | y | ≤ | 6 |
x | − | y | ≥ |
−6. |
minimum:
p=
(x,y)=
maximum:
p=
(x,y)=
c) Maximize p = x − 2y subject to
x | + | 3y | ≤ | 7 |
x | − | 4y | ≤ | 0 |
6x | − | 3y | ≥ | 0 |
x ≥ 0, y ≥ 0 |
p=
(x,y)=
Solve the LP problem. If no optimal solution exists, indicate whether the feasible region is empt...
Solve the LP problem. If no optimal solution exists, indicate whether the feasible region is empty or the objective function is unbounded. HINT (See Example 1.] (Enter EMPTY if the region is empty. Enter UNBOUNDED if the function is unbounded.) Minimize c = 8x - By subject to 7 sy ys 2x x + y27 x + 2y = 16 x>0, y 2 0. c= (x,y) = ((
Solve the LP problem. If no optimal solution exists, indicate whether the feasible region is empty or the objective function is unbounded. HINT [See Example 1.] (Enter EMPTY if the region is empty. Enter UNBOUNDED if the function is unbounded.) Minimize c = x + y subject to x + 5y ≥ 6 5x + y ≥ 6 x ≥ 0, y ≥ 0. c = x = y =
Solve the given linear programming problem using the simplex method. If no optimal solution exists, indicate whether the feasible region is empty or the objective function is unbounded. (Enter EMPTY if the feasible region is empty and UNBOUNDED if the objective function is unbounded.) Minimize c = x + y + z + w subject to x + y ≥ 80 x + z ≥ 60 x + y − w ≤ 50 y + z − w ≤ 50...
Maximize and minimize p = 2x − y subject to x + y ≥ 1 x − y ≤ 1 x − y ≥ −1 x ≤ 7, y ≤ 7. Solve the LP problem. If no optimal solution exists, indicate whether the feasible region is empty or the objective function is unbounded. HINT (See Example 1.] (Enter EMPTY if the region is empty. Enter UNBOUNDED if the function is unbounded.) Maximize and minimize p = 2x - y subject...
Solve by Linear Programming. (Be sure to show the graph of the feasible region, the appropriate vertices, optimal value, AND SHOW ALL WORK!.) Exercise 1 LP 1. Maximize: C = x – y Constraints: x ≥ 0, and y ≥ 0 x + 3y ≤ 120 3x + y ≤ 120 Exercise 2 LP 2. Maximize: C = 3x + 4y Constraints: x + y ≤ 10 – x + y ≤ 5 2x + 4y ≤ 32
4. Given the following linear programming problem, determine which situation (choose one) a. An optimal solution exists at a single vertex point. b. There is more than one optimal solution. C. There is no optimal solution because the feasible region does not exist d. There is no optimal solution because the feasible region is unbounded. Maximize: 2x +3y Subject to: x +2y 28 5. Graph the inequality: 2x +3y >12 6. Graph the system of inequalities: 7. Graph the system...
. Solve the following LP minimization problem. Min 3X + 2Y s.t. 5X + 3Y <= 30 3X + 4Y >= 36 Y >= 7 X , Y >= 0 Group of answer choices X = 0, Y= 9 The optimal value of the objective function is 5. None of the other answers are correct. The optimal value of the objective function is 7. X = 1,...
Consider the following constraints and the c g graph below: Constraint L:4x-y21 Constraint 2: x+ys4 Constraint 3:-x-4y 2-8 x, y20 4x-y=1 x-4y -8 a. (2 points) Shade the feasible region in the graph provided above. b. (1 point) For this part only the objective function is Minimize -2x + y. Which of the following describes the optimal solution? (Put a check next to your answer) Infeasible solution Unique optimal solution the point (4,0) minimizes the LP Alternate optimal solution Unbounded...
0/2 POINTS PREVIOUS ANSWERS WANEFM7 5.R.005. Solve the given linear programming problem graphically. (Enter EMPTY if the region is empty. Enter UNBOUNDED If the function is unbounded.) Maximize p = 2x + y subject to 3x + y s 30 x + y s 12 x + 3y = 30 X 20, y 20. (X,Y) - Submit Answer
Maximize P = 4x + 5y subject to 2x + y < 50 2 + 3y < 75 2 > 0 y > 0 Identify the feasible region as bounded or unbounded: List the corner points of the feasible region, separated by a comma and a space. If the region is unbounded, create appropriate ghost points and list those as well. For each corner point, list the value of the objective function at that point. The format should be (x1,y1)...