Q.Solve the following linear programming problem graphically: Minimize subject to the constraints: , , , , .
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Start your 14-day free trial to unlock the full solution →To minimize the objective function subject to the given linear constraints, we use the graphical method. This involves plotting the constraint lines, identifying the feasible region, and evaluating at its corner points. The minimum value of is 300, occurring at the point .
Linear Programming Problems (LPPs) involve optimizing (maximizing or minimizing) a linear objective function subject to a set of linear inequalities called constraints. When there are only two decision variables (typically and ), we can solve these problems using the graphical method.
The core idea behind the graphical method is that the set of all points satisfying all the constraints simultaneously forms a region called the feasible region. This region is always a convex polygon (or an unbounded convex region). A fundamental theorem in linear programming states that if an optimal solution (maximum or minimum) exists, it will always occur at one of the corner points (vertices) of this feasible region.
Therefore, our strategy is to:
- Graph each constraint as a line.
- Identify the feasible region by determining which side of each line satisfies the inequality.
- Find the coordinates of all the corner points of this feasible region.
- Substitute these corner point coordinates into the objective function to find the corresponding values.
- Select the minimum (or maximum, depending on the problem) value among these values.
Let's apply this step-by-step to the given problem:
Minimize
Subject to:
1. Convert Inequalities to Equations and Plot the Lines
To graph the constraints, we first treat each inequality as an equality to find the boundary lines.
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Constraint 1:
- If , . Point: .
- If , . Point: .
- Plot the line passing through and .
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Constraint 2:
- If , . Point: .
- If , . Point: .
- Plot the line passing through and .
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Constraint 3: (or )
- If , . Point: .
- If , . Point: .
- Plot the line passing through and .
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Constraints 4 & 5: and
These imply that our feasible region must lie entirely in the first quadrant of the coordinate plane.
2. Identify the Feasible Region
Now we determine which side of each line satisfies its corresponding inequality. We can do this by testing a point (like the origin if the line does not pass through it).
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For :
Test : . This is true. So, the feasible region lies on the side of the line that includes the origin.
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For :
Test : . This is false. So, the feasible region lies on the side of the line that does not include the origin.
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For :
This line passes through the origin, so we cannot use as a test point. Let's test : . This is true. So, the feasible region lies on the side of the line that includes the point (i.e., to the right of the line).
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For and :
The feasible region is restricted to the first quadrant.
The feasible region is the area that satisfies all these conditions simultaneously. Graphing these lines and shading the appropriate regions will reveal a polygon.
3. Determine the Corner Points of the Feasible Region
The corner points are the vertices of the feasible region, formed by the intersection of the boundary lines. We need to find the coordinates of these intersection points.
Let's label the lines:
- (y-axis)
- (x-axis)
The feasible region is a quadrilateral with the following vertices:
- Point A: Intersection of and
- …
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