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31
A constraint in an LP model becomes redundant because.
Discuss
Answer & Solution
Answer: Option D
Solution:
A redundant constraint is a constraint that can be omitted from the system without changing the set of feasible solutions S. An implicit equality constraint is an inequality constraint that can be replaced by an equality constraint without changing S.
32
If two constraints do not intersect in the positive quadrant of the graph, then.
Discuss
Answer & Solution
Answer: Option A
Solution:
If two constraints do not intersect in the positive quadrant of the graph, then the problem is infeasible.
33
Constraints in LP problem are called active if they.
Discuss
Answer & Solution
Answer: Option A
Solution:
Constraints in LP problem are called active if they Represent optimal solution. An optimal solution that lies at the intersection. point of two constraints causes both of those constraints to be considered active.
34
The solution space (region) of an LP problem is unbounded due to.
Discuss
Answer & Solution
Answer: Option C
Solution:
An infeasible problem is a problem that has no solution while an unbounded problem is one where the constraints do not restrict the objective function and the optimal objective goes to infinity. Both situations arise due to errors or shortcomings in the formulation or in the data defining the problem.
35
While solving a LP model graphically, the area bounded by the constraints is called?
Discuss
Answer & Solution
Answer: Option A
Solution:
While solving a LP model graphically, the area bounded by the constraints is called feasible region. It is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints.
36
Alternative solutions exist of an LP model when.
Discuss
Answer & Solution
Answer: Option B
Solution:
Alternative solutions exist of an LP model when objective function equation is parallel to one of the constraints. Linear programming (LP, also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
37
While solving a LP problem, infeasibility may be removed by?
Discuss
Answer & Solution
Answer: Option C
Solution:
While solving a LP problem, infeasibility may be removed by removing a constraint. A linear program is infeasible if there exists no solution that satisfies all of the constraints in other words, if no feasible solution can be constructed.
38
If a non-redundant constraint is removed from an LP problem then.
Discuss
Answer & Solution
Answer: Option A
Solution:
If a non-redundant constraint is removed from an LP problem then feasible region will become larger. A redundant constraint is a constraint that can be omitted from the system without changing the set of feasible solutions S. An implicit equality constraint is an inequality constraint that can be replaced by an equality constraint without changing S.
39
If one of the constraint of an equation in an LP problem has an unbounded solution, then.
Discuss
Answer & Solution
Answer: Option B
Solution:
If one of the constraint of an equation in an LP problem has an unbounded solution, then feasible region should have a line segment. If there is going to be an optimal solution to a linear programming problem, it will occur at one or more corner points, or on a line segment between two corner points.
40
Customer behavior in which the customer moves from one queue to another in a multiple channel situation is.
Discuss
Answer & Solution
Answer: Option C
Solution:
Customer behavior in which the customer moves from one queue to another in a multiple channel situation is Jockeying. Customers may jockey from one line to another, i.e. move from one line to another. This can be seen typically at supermarkets as well as train stations, where a person leaves the line he is standing in, and joins another line which appears to be shorter, or appears to be moving faster.