88552
If subject to then is maximum at the point is maximum at the point
1
2
3
4
Explanation:
(A) : Given, Subject to Using graphical method we get Solve and we get We solve to get corner points and as follows. For point solve and We get Now calculate value to as follows: At Point A At Point B At Point At Point At Point So the max value of is 95 which is at point .
MHT CET-2020
Linear Inequalities and Linear Programming
88553
The L.P.P. to maximize subject to has
1 No solution
2 One solution
3 Two solutions
4 Infinite solutions
Explanation:
(A) : Given, subject to 0 Using graphical method, we get - So, we do not get any Corner point so, the system has no solution.
MHT CET-2020
Linear Inequalities and Linear Programming
88554
The objective function , subject to has minimum value at the point
1 On X - axis
2 On Y - axis
3 At the origin
4 On the use parallel to -axis
Explanation:
(A) : Given, subject to , and Using graphical method, we get - Let as calculate point solve and we get point as The point is Similarly we find point as follows Solve and We get The point is Point is point . and Point D is Now, at Point at Point B at Point at Point minimum value is 14 which is point , which is on the axis.
MHT CET-2017
Linear Inequalities and Linear Programming
88555
The shaded region is the solution set of the inequalities.
1
2
3
4
Explanation:
(C) : In the given figure and Let us find the equation of line passing through Point and or Therefore, So, we get
88552
If subject to then is maximum at the point is maximum at the point
1
2
3
4
Explanation:
(A) : Given, Subject to Using graphical method we get Solve and we get We solve to get corner points and as follows. For point solve and We get Now calculate value to as follows: At Point A At Point B At Point At Point At Point So the max value of is 95 which is at point .
MHT CET-2020
Linear Inequalities and Linear Programming
88553
The L.P.P. to maximize subject to has
1 No solution
2 One solution
3 Two solutions
4 Infinite solutions
Explanation:
(A) : Given, subject to 0 Using graphical method, we get - So, we do not get any Corner point so, the system has no solution.
MHT CET-2020
Linear Inequalities and Linear Programming
88554
The objective function , subject to has minimum value at the point
1 On X - axis
2 On Y - axis
3 At the origin
4 On the use parallel to -axis
Explanation:
(A) : Given, subject to , and Using graphical method, we get - Let as calculate point solve and we get point as The point is Similarly we find point as follows Solve and We get The point is Point is point . and Point D is Now, at Point at Point B at Point at Point minimum value is 14 which is point , which is on the axis.
MHT CET-2017
Linear Inequalities and Linear Programming
88555
The shaded region is the solution set of the inequalities.
1
2
3
4
Explanation:
(C) : In the given figure and Let us find the equation of line passing through Point and or Therefore, So, we get
88552
If subject to then is maximum at the point is maximum at the point
1
2
3
4
Explanation:
(A) : Given, Subject to Using graphical method we get Solve and we get We solve to get corner points and as follows. For point solve and We get Now calculate value to as follows: At Point A At Point B At Point At Point At Point So the max value of is 95 which is at point .
MHT CET-2020
Linear Inequalities and Linear Programming
88553
The L.P.P. to maximize subject to has
1 No solution
2 One solution
3 Two solutions
4 Infinite solutions
Explanation:
(A) : Given, subject to 0 Using graphical method, we get - So, we do not get any Corner point so, the system has no solution.
MHT CET-2020
Linear Inequalities and Linear Programming
88554
The objective function , subject to has minimum value at the point
1 On X - axis
2 On Y - axis
3 At the origin
4 On the use parallel to -axis
Explanation:
(A) : Given, subject to , and Using graphical method, we get - Let as calculate point solve and we get point as The point is Similarly we find point as follows Solve and We get The point is Point is point . and Point D is Now, at Point at Point B at Point at Point minimum value is 14 which is point , which is on the axis.
MHT CET-2017
Linear Inequalities and Linear Programming
88555
The shaded region is the solution set of the inequalities.
1
2
3
4
Explanation:
(C) : In the given figure and Let us find the equation of line passing through Point and or Therefore, So, we get
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Linear Inequalities and Linear Programming
88552
If subject to then is maximum at the point is maximum at the point
1
2
3
4
Explanation:
(A) : Given, Subject to Using graphical method we get Solve and we get We solve to get corner points and as follows. For point solve and We get Now calculate value to as follows: At Point A At Point B At Point At Point At Point So the max value of is 95 which is at point .
MHT CET-2020
Linear Inequalities and Linear Programming
88553
The L.P.P. to maximize subject to has
1 No solution
2 One solution
3 Two solutions
4 Infinite solutions
Explanation:
(A) : Given, subject to 0 Using graphical method, we get - So, we do not get any Corner point so, the system has no solution.
MHT CET-2020
Linear Inequalities and Linear Programming
88554
The objective function , subject to has minimum value at the point
1 On X - axis
2 On Y - axis
3 At the origin
4 On the use parallel to -axis
Explanation:
(A) : Given, subject to , and Using graphical method, we get - Let as calculate point solve and we get point as The point is Similarly we find point as follows Solve and We get The point is Point is point . and Point D is Now, at Point at Point B at Point at Point minimum value is 14 which is point , which is on the axis.
MHT CET-2017
Linear Inequalities and Linear Programming
88555
The shaded region is the solution set of the inequalities.
1
2
3
4
Explanation:
(C) : In the given figure and Let us find the equation of line passing through Point and or Therefore, So, we get