1)A constraint either indirectly or directly limits Decision variables. Objectiv
ID: 469090 • Letter: 1
Question
1)A constraint either indirectly or directly limits
Decision variables.
Objective function.
Neither answer (a) nor answer (b).
Both answer (a) and answer (b).
2A zero shadow price on an active constraint indicates:
The existence of alternative optimal solutions.
The problem has alternative optimal solutions.
The problem is infeasible.
The problem is unbounded.
3The range of feasibility is when the:
Value of the shadow prices remain valid.
Value of the shadow prices always equals zero.
Value of the shadow prices always is negative.
Value of the shadow prices is always increasing
4An optimal solution of a minimization problem is:
An extreme point closest to the origin.
An infeasible point closest to the extreme constraint.
An extreme point farthest from the origin.
A feasible point farthest from the origin.
Decision variables.
Objective function.
Neither answer (a) nor answer (b).
Both answer (a) and answer (b).
Explanation / Answer
1)
A constraint either indirectly or directly limits
In the optimization model, the value of objective function is limited by the type of constraint. The optimal value of decision variables also depends on constraint amount. Thus, constraint directly or indirectly limits the decision variable value and objective function.
Correct option: Both answer (a) and answer (b).
2)
A zero shadow price on an active constraint indicates
Active constraints are binding constraints which are utilized completely. If the shadow price of binding constraint is zero its means the problem as alternative solution.
Correct option: The problem has alternative optimal solutions.
3)
In sensitivity analysis of LPP, allowable decrease or increase in the RHS of constraint is feasible when the shadow prices remain valid.
Correct Option: Value of the shadow prices remains valid.
4)
The LP problem with minimization tends to minimize its objective function. To minimize the function, the decision variables should be small as possible. Thus, the extreme point of the feasible region of minimization problem is closest to origin.
Correct Option: An extreme point closest to the origin.
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.