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Z = 3x + 9y x + 3y le 60, x + y ge 10,...

`Z = 3x + 9y`
`x + 3y le 60, x + y ge 10, x le y , x ge 0, y ge 0`

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To solve the linear programming problem given by the objective function \( Z = 3x + 9y \) with the constraints: 1. \( x + 3y \leq 60 \) 2. \( x + y \geq 10 \) 3. \( x \leq y \) 4. \( x \geq 0 \) 5. \( y \geq 0 \) we will follow these steps: ### Step 1: Identify the Constraints We have the following constraints: - \( x + 3y \leq 60 \) - \( x + y \geq 10 \) - \( x \leq y \) - \( x \geq 0 \) - \( y \geq 0 \) ### Step 2: Convert Inequalities to Equations To find the boundary lines, we convert the inequalities into equations: 1. \( x + 3y = 60 \) 2. \( x + y = 10 \) 3. \( x = y \) ### Step 3: Find Intercepts For each equation, we will find the x-intercept and y-intercept. 1. **For \( x + 3y = 60 \)**: - x-intercept: Set \( y = 0 \) → \( x = 60 \) → Point: \( (60, 0) \) - y-intercept: Set \( x = 0 \) → \( 3y = 60 \) → \( y = 20 \) → Point: \( (0, 20) \) 2. **For \( x + y = 10 \)**: - x-intercept: Set \( y = 0 \) → \( x = 10 \) → Point: \( (10, 0) \) - y-intercept: Set \( x = 0 \) → \( y = 10 \) → Point: \( (0, 10) \) 3. **For \( x = y \)**: - This line passes through the origin and has points like \( (0, 0) \), \( (1, 1) \), etc. ### Step 4: Graph the Constraints Now we will graph the lines and shade the feasible region based on the inequalities: - For \( x + 3y \leq 60 \), shade below the line. - For \( x + y \geq 10 \), shade above the line. - For \( x \leq y \), shade below the line \( x = y \). - The feasible region is where all shaded areas overlap and is bounded by the axes. ### Step 5: Identify Corner Points The corner points of the feasible region can be found by solving the equations at their intersections: 1. Intersection of \( x + 3y = 60 \) and \( x + y = 10 \): - From \( x + y = 10 \), we can express \( x = 10 - y \). - Substitute into \( x + 3y = 60 \): \[ (10 - y) + 3y = 60 \implies 10 + 2y = 60 \implies 2y = 50 \implies y = 25 \implies x = 10 - 25 = -15 \text{ (not feasible)} \] 2. Intersection of \( x + 3y = 60 \) and \( x = y \): - Substitute \( y \) for \( x \): \[ y + 3y = 60 \implies 4y = 60 \implies y = 15 \implies x = 15 \text{ (point: (15, 15))} \] 3. Intersection of \( x + y = 10 \) and \( x = y \): - Substitute \( y \) for \( x \): \[ y + y = 10 \implies 2y = 10 \implies y = 5 \implies x = 5 \text{ (point: (5, 5))} \] 4. The feasible points are \( (0, 20) \), \( (0, 10) \), \( (5, 5) \), and \( (15, 15) \). ### Step 6: Evaluate the Objective Function at Corner Points Now we evaluate \( Z = 3x + 9y \) at each corner point: 1. At \( (0, 20) \): \( Z = 3(0) + 9(20) = 180 \) 2. At \( (0, 10) \): \( Z = 3(0) + 9(10) = 90 \) 3. At \( (5, 5) \): \( Z = 3(5) + 9(5) = 60 \) 4. At \( (15, 15) \): \( Z = 3(15) + 9(15) = 180 \) ### Step 7: Determine Maximum and Minimum Values - Maximum \( Z = 180 \) at points \( (0, 20) \) and \( (15, 15) \). - Minimum \( Z = 60 \) at point \( (5, 5) \). ### Conclusion - Maximum value of \( Z \) is \( 180 \) at points \( (0, 20) \) and \( (15, 15) \). - Minimum value of \( Z \) is \( 60 \) at point \( (5, 5) \).
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MODERN PUBLICATION-LINEAR PROGRAMMING -EXERCISE 12(b) (Long Answer Tyoe Questions(I)) (LATQ)
  1. Z= 4x + 7y x + 2y le 20, x + y le 15, x ge 0, y ge 0.

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  2. Z = -3x + 4y x + 2y le 8, 3x + 2y le 12, x ge 0 , y ge 0.

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  3. Z = 6x + 11y 2x + y le 104, x + 2y le 76, x, y ge 0

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  4. Z = 7x + 4y 2x + y le 10, x + 2y le 12, x ge 0, y ge 0

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  5. (i) Z = 20x + 10y x + 2y le 28, 3x + y le 24, x ge 2, x, y ge 0 (ii...

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  6. Minimize (16-21): OBJECTIVE FUNCTION CONSTRAINTS Z = 200x + 500y ...

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  7. Z = -3x + 4y x + 2y le 8, 3x + 2y le 12, x ge 0, y ge 0

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  8. Z = 3x + 5y x + 3y ge 3, x + y ge 2,x ge 0, y ge 0

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  9. Z = 2x + 3y x ge 0, y ge 0, 1 le x + 2y le10

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  10. Z = 3x + 9y x + 3y le 60, x + y ge 10, x le y , x ge 0, y ge 0

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  11. Z = 5x + 10y x + y ge 60, x + 2y le 120, x -2y ge 0, x, y ge 0

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  12. Maximize if possible: (i) Z = 3x + 2y subject to the constraints: x ...

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  13. Maximize: Z = -x + 2y, subject to the constraints: x ge 3, x + y ...

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  14. Maximize : Z = x + y,subject to the constraints: x - y le -1, -x +...

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  15. Minimize and Maximize(25-29): OBJECTIVE FUNCTION CONSTRAINTS Z = ...

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  16. Z = 5x + 10y x + 2y le 120, x + y ge 60, x - 2y ge 0, x ge 0 , y ge ...

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  17. Z = 15x + 30y x + y le 8, 2x + y ge 8, x - 2y ge 0, x, y ge 0

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  18. Z = x + 2y x + 2y ge 100, x - y le 0, 2x + y le 200, x, y ge 0

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  19. (i)Z = 3x + 2y x + 3y le 60, x + y ge 10, x le y, x, y ge 0 (ii)Z = ...

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  20. Consider the following LPP: Maximize Z = 3x + 2y subject to the cons...

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