88590
What is the area of the region enclosed by the inequalities \(x \geq 0, y \geq 0,4 x-y+4 \leq 0\) and \(x-\) \(3 \mathbf{y} \geq 0\) ?
1 Null
2 6 sq. units
3 12 sq. units
4 18 sq. units
Explanation:
(A) : We have to find the region enclosed by the inequalities \(x \geq 0, y \geq 0\) \(4 x-y+4 \leq 0 \text { and } x-3 y \geq 0\) According to the area is null by above inequalities
J&K CET-2019
Linear Inequalities and Linear Programming
88577
The objective function of LPP defined over the convex set attains its optimum value at
1 At least two of the corner points
2 All the corner points
3 At least one of the corner points
4 None of the corner points
Explanation:
(C) : In LPP. objective function is a function which is to be maximized or minimized subject to the given constraints and the optimum value is the value which is to be maximized or minimized value at one of the corner point of \(\mathrm{AB}\).
MHT CET-2017
Linear Inequalities and Linear Programming
88575
If the constraints in a linear programming problem are changed then
1 The problem is to be re-evaluated.
2 Solution is not defined.
3 The objective function has to be modified.
4 The change in constraints is ignored.
Explanation:
(A) : Optimization of the objective function of an LPP is governed by its constraints. Therefore, if the constraints in a linear programming problem are changed, then the problem needs to be re-evaluated.
BITSAT-2018
Linear Inequalities and Linear Programming
88593
The objective function of L.L.P defined over the convex set attains its optimum value at
1 none of the corner points.
2 all the corner points.
3 at least two of the corner points.
4 at least one of the corner points.
Explanation:
(D) : Suppose that \(\mathrm{z}=\mathrm{ax}+\) by be the objective function when \(z\) has optimum value (maximum or minimum), where the variables \(\mathrm{x}\) and \(\mathrm{y}\) are subjected to constraints described by linear inequalities, this optimum value must occur at a corner points of the feasible region. Thus, the function attains its optimum value at one of the corner points.
88590
What is the area of the region enclosed by the inequalities \(x \geq 0, y \geq 0,4 x-y+4 \leq 0\) and \(x-\) \(3 \mathbf{y} \geq 0\) ?
1 Null
2 6 sq. units
3 12 sq. units
4 18 sq. units
Explanation:
(A) : We have to find the region enclosed by the inequalities \(x \geq 0, y \geq 0\) \(4 x-y+4 \leq 0 \text { and } x-3 y \geq 0\) According to the area is null by above inequalities
J&K CET-2019
Linear Inequalities and Linear Programming
88577
The objective function of LPP defined over the convex set attains its optimum value at
1 At least two of the corner points
2 All the corner points
3 At least one of the corner points
4 None of the corner points
Explanation:
(C) : In LPP. objective function is a function which is to be maximized or minimized subject to the given constraints and the optimum value is the value which is to be maximized or minimized value at one of the corner point of \(\mathrm{AB}\).
MHT CET-2017
Linear Inequalities and Linear Programming
88575
If the constraints in a linear programming problem are changed then
1 The problem is to be re-evaluated.
2 Solution is not defined.
3 The objective function has to be modified.
4 The change in constraints is ignored.
Explanation:
(A) : Optimization of the objective function of an LPP is governed by its constraints. Therefore, if the constraints in a linear programming problem are changed, then the problem needs to be re-evaluated.
BITSAT-2018
Linear Inequalities and Linear Programming
88593
The objective function of L.L.P defined over the convex set attains its optimum value at
1 none of the corner points.
2 all the corner points.
3 at least two of the corner points.
4 at least one of the corner points.
Explanation:
(D) : Suppose that \(\mathrm{z}=\mathrm{ax}+\) by be the objective function when \(z\) has optimum value (maximum or minimum), where the variables \(\mathrm{x}\) and \(\mathrm{y}\) are subjected to constraints described by linear inequalities, this optimum value must occur at a corner points of the feasible region. Thus, the function attains its optimum value at one of the corner points.
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Linear Inequalities and Linear Programming
88590
What is the area of the region enclosed by the inequalities \(x \geq 0, y \geq 0,4 x-y+4 \leq 0\) and \(x-\) \(3 \mathbf{y} \geq 0\) ?
1 Null
2 6 sq. units
3 12 sq. units
4 18 sq. units
Explanation:
(A) : We have to find the region enclosed by the inequalities \(x \geq 0, y \geq 0\) \(4 x-y+4 \leq 0 \text { and } x-3 y \geq 0\) According to the area is null by above inequalities
J&K CET-2019
Linear Inequalities and Linear Programming
88577
The objective function of LPP defined over the convex set attains its optimum value at
1 At least two of the corner points
2 All the corner points
3 At least one of the corner points
4 None of the corner points
Explanation:
(C) : In LPP. objective function is a function which is to be maximized or minimized subject to the given constraints and the optimum value is the value which is to be maximized or minimized value at one of the corner point of \(\mathrm{AB}\).
MHT CET-2017
Linear Inequalities and Linear Programming
88575
If the constraints in a linear programming problem are changed then
1 The problem is to be re-evaluated.
2 Solution is not defined.
3 The objective function has to be modified.
4 The change in constraints is ignored.
Explanation:
(A) : Optimization of the objective function of an LPP is governed by its constraints. Therefore, if the constraints in a linear programming problem are changed, then the problem needs to be re-evaluated.
BITSAT-2018
Linear Inequalities and Linear Programming
88593
The objective function of L.L.P defined over the convex set attains its optimum value at
1 none of the corner points.
2 all the corner points.
3 at least two of the corner points.
4 at least one of the corner points.
Explanation:
(D) : Suppose that \(\mathrm{z}=\mathrm{ax}+\) by be the objective function when \(z\) has optimum value (maximum or minimum), where the variables \(\mathrm{x}\) and \(\mathrm{y}\) are subjected to constraints described by linear inequalities, this optimum value must occur at a corner points of the feasible region. Thus, the function attains its optimum value at one of the corner points.
88590
What is the area of the region enclosed by the inequalities \(x \geq 0, y \geq 0,4 x-y+4 \leq 0\) and \(x-\) \(3 \mathbf{y} \geq 0\) ?
1 Null
2 6 sq. units
3 12 sq. units
4 18 sq. units
Explanation:
(A) : We have to find the region enclosed by the inequalities \(x \geq 0, y \geq 0\) \(4 x-y+4 \leq 0 \text { and } x-3 y \geq 0\) According to the area is null by above inequalities
J&K CET-2019
Linear Inequalities and Linear Programming
88577
The objective function of LPP defined over the convex set attains its optimum value at
1 At least two of the corner points
2 All the corner points
3 At least one of the corner points
4 None of the corner points
Explanation:
(C) : In LPP. objective function is a function which is to be maximized or minimized subject to the given constraints and the optimum value is the value which is to be maximized or minimized value at one of the corner point of \(\mathrm{AB}\).
MHT CET-2017
Linear Inequalities and Linear Programming
88575
If the constraints in a linear programming problem are changed then
1 The problem is to be re-evaluated.
2 Solution is not defined.
3 The objective function has to be modified.
4 The change in constraints is ignored.
Explanation:
(A) : Optimization of the objective function of an LPP is governed by its constraints. Therefore, if the constraints in a linear programming problem are changed, then the problem needs to be re-evaluated.
BITSAT-2018
Linear Inequalities and Linear Programming
88593
The objective function of L.L.P defined over the convex set attains its optimum value at
1 none of the corner points.
2 all the corner points.
3 at least two of the corner points.
4 at least one of the corner points.
Explanation:
(D) : Suppose that \(\mathrm{z}=\mathrm{ax}+\) by be the objective function when \(z\) has optimum value (maximum or minimum), where the variables \(\mathrm{x}\) and \(\mathrm{y}\) are subjected to constraints described by linear inequalities, this optimum value must occur at a corner points of the feasible region. Thus, the function attains its optimum value at one of the corner points.