Q.For a linear programming problem, the objective function Z=3x+9y has the corner points of the bounded feasible region (0,10), (5,5), (15,15) and (0,20). The maximum value of Z is ____.
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Multiple Optimal Solutions
Imagine climbing to the highest point of a mountain range and finding two peaks of exactly the same height, joined by a flat ridge. You have not found one best spot — you have found many, all equally high. That is the picture behind multiple optimal solutions: a problem where more than one choice gives the same best value of the objective.
A concrete example
Maximise Z=2x+2y subject to x+y≤10, x,y≥0.
Since Z=2x+2y=2(x+y) and x+y≤10, the largest value is Z=20. But which point achieves it? Every point on the line x+y=10 in the first quadrant — (10,0), (0,10), (5,5), (3,7) — gives Z=20. There is not one optimal point but a whole edge of optimal points.
Why it happens
In graphical linear programming, multiple optimal solutions occur when the objective line is parallel to one of the boundary edges of the feasible region. As you slide the objective line outward, its final contact with the region is that whole edge, not a single corner — so every point on the edge (including both its corner endpoints) is optimal.
How to recognise it
Using the graphical method:
- Draw the feasible region.
- Draw the objective line ax+by=constant for any value.
- Slide it parallel to itself in the direction of improvement.
- If the last contact is a line segment rather than a single corner, the problem has multiple optimal solutions.
A quick algebraic hint: if the objective Z=ax+by gives the same optimal value at two adjacent corners, then every point on the edge joining them is also optimal.
Why it matters …
Evaluating Z at every corner point shows two adjacent corners tie for the largest value, meaning the maximum is attained along the whole segment joining them, not at a single point. …
Evaluate Z at every corner point; if two adjacent corners tie for the maximum, every point on the segment joining them is also optimal.
Z=3x+9y: at (0,10), Z=90; at (5,5), Z=60; at (15,15), Z=45+135=180; at (0,20), Z=180.
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- CBSE 2023Set 65/3/11 markMCQQ.The number of feasible solutions of the linear programming problem given as Maximize z=15x+30y subject to constraints : 3x+y≤12, x+2y≤10, x≥0, y≥0 is(a) 1(b) 2(c) 3(d) infinite
›Reveal solutionSolution
When the objective function's slope matches the slope of a binding constraint that forms an edge of the feasible region, all points along that edge are optimal solutions, leading to an infinite number of feasible solutions. The maximum value of z is 150, achieved at infinitely many points.
In a Linear Programming Problem (LPP), we aim to maximize or minimize an objective function subject to a set of linear constraints. The set of all points satisfying these constraints is called the feasible region. This region is always a convex polygon. A fundamental theorem of LPP states that if an optimal solution exists, it will occur at one of the corner points (vertices) of this feasible region.
However, it is possible for an LPP to have multiple optimal solutions. This occurs when the objective function line is parallel to one of the edges of the feasible region, and that edge lies on the boundary of the optimal value. In such a scenario, every point on that entire edge segment, including its two corner points, will yield the same optimal value. Since a line segment contains infinitely many points, there will be infinitely many optimal solutions.
Let's solve the given problem step-by-step.
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Graph the Feasible Region:
We need to plot the lines corresponding to the given constraints and identify the region that satisfies all inequalities.
- 3x+y≤12 (Let's call the line L1:3x+y=12)
- If x=0, y=12. Point: (0,12)
- If y=0, 3x=12⟹x=4. Point: (4,0)
- x+2y≤10 (Let's call the line L2:x+2y=10)
- If x=0, 2y=10⟹y=5. Point: (0,5)
- If y=0, x=10. Point: (10,0)
- x≥0 (This means the feasible region is to the right of the y-axis)
- y≥0 (This means the feasible region is above the x-axis)
The feasible region is bounded by these lines and the axes. We need to find the corner points of this region.
- 3x+y≤12 (Let's call the line L1:3x+y=12)
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Identify the Corner Points (Vertices):
The corner points are the intersections of these lines within the first quadrant (x≥0,y≥0).
- Origin: O=(0,0) (Intersection of x=0 and y=0)
- Intersection of L1 and y=0: 3x+0=12⟹x=4. Point: A=(4,0)
- Intersection of L2 and x=0: 0+2y=10⟹y=5. Point: C=(0,5)
- Intersection of L1 and L2:
We solve the system of equations:
- 3x+y=12
- x+2y=10 From (1), y=12−3x. Substitute this into (2): x+2(12−3x)=10 x+24−6x=10 −5x=10−24 −5x=−14 x=514 Now find y: y=12−3(514)=12−542=560−42=518 Point: B=(514,518) or (2.8,3.6)
The feasible region is the polygon OABC with vertices (0,0), (4,0), (14/5,18/5), and (0,5).
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Evaluate the Objective Function at Each Corner Point:
The objective function is z=15x+30y. We calculate its value at each vertex:
Corner Point (x,y) Value of z=15x+30y O=(0,0) 15(0)+30(0)=0 A=(4,0) 15(4)+30(0)=60 B=(14/5,18/5) 15(14/5)+30(18/5)=3(14)+6(18)=42+108=150 C=(0,5) 15(0)+30(5)=150 -
Determine the Maximum Value and Optimal Solutions: …
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