Decision Science | Chapter 3 | Part 3 | MBA MCQs | DS

Decision Science MCQs

  

 

1. The best use of linear programming technique is to find an optimal use of
   1.   Money
   2.   Manpower
   3.   Machine
   4.   All of the above
2. Which of the following is not a characteristic of the LP
   1.   Resources must be limited
   2.   only one objective function
   3.   Parameters value remains constant during the planning period
   4.   The problem must be of minimization type
3. Non-negativity condition in an LP model implies
   1.   A positive coefficient of variables in objective function
   2.   A positive coefficient of variables in any constraint
   3.   Non-negative value of resources
   4.   None of the above
4. Which of the following is an assumption of an LP model
   1.   Divisibility
   2.   Proportionality
   3.   Additivity
   4.   All of the above
5. Which of the following is a limitation associated with an LP model
   1.   The relationship among decision variables in linear
   2.   No guarantee to get integer valued solutions
   3.   No consideration of effect of time & uncertainty on LP model
   4.   All of the above
6. The graphical method of LP problem uses
   1.   Objective function equation
   2.   Constraint equations
   3.   Linear equations
   4.   All of the above
7. A feasible solution to an LP problem
   1.   Must satisfy all of the problem’s constraints simultaneously
   2.   Need not satisfy all of the constraints, only some of them
   3.   Must be a corner point of the feasible region
   4.   Must optimize the value of the objective function
8. Which of the following statements is true with respect to the optimal solution of an LP problem
   1.   Every LP problem has an optimal solution
   2.   Optimal solution of an LP problem always occurs at an extreme point
   3.   At optimal solution all resources are completely used
   4.   If an optimal solution exists, there will always be at least one at a corner
9. An iso-profit line represents
   1.   An infinite number of solutions all of which yield the same profit
   2.   An infinite number of solution all of which yield the same cost
   3.   An infinite number of optimal solutions
   4.   A boundary of the feasible region
10. If an iso-profit line yielding the optimal solution coincides with a constaint line, then
    1.   The solution is unbounded
    2.   The solution is infeasible
    3.   The constraint which coincides is redundant
    4.   None of the above
11. While plotting constraints on a graph paper, terminal points on both the axes are connected by a straight line because
    1.   The resources are limited in supply
    2.   The objective function as a linear function
    3.   The constraints are linear equations or inequalities
    4.   All of the above
12. A constraint in an LP model becomes redundant because
    1.   Two iso-profit line may be parallel to each other
    2.   The solution is unbounded
    3.   This constraint is not satisfied by the solution values
    4.   None of the above
13. If two constraints do not intersect in the positive quadrant of the graph, then
    1.   The problem is infeasible
    2.   The solution is unbounded
    3.   One of the constraints is redundant
    4.   None of the above
14. Constraints in LP problem are called active if they
    1.   Represent optimal solution
    2.   At optimality do not consume all the available resources
    3.   Both a & b
    4.   None of the above
15. The solution space (region) of an LP problem is unbounded due to
    1.   An incorrect formulation of the LP model
    2.   Objective function is unbounded
    3.   Neither a nor b
    4.   Both a & b
16. While solving a LP model graphically, the area bounded by the constraints is called
    1.   Feasible region
    2.   Infeasible region
    3.   Unbounded solution
    4.   None of the above
17. Alternative solutions exist of an LP model when
    1.   One of the constraints is redundant
    2.   Objective function equation is parallel to one of the constraints
    3.   Two constraints are parallel
    4.   All of the above
18. While solving a LP problem, infeasibility may be removed by
    1.   Adding another constraint
    2.   Adding another variable
    3.   Removing a constraint
    4.   Removing a variable
19. If a non-redundant constraint is removed from an LP problem then
    1.   Feasible region will become larger
    2.   Feasible region will become smaller
    3.   Solution will become infeasible
    4.   None of the above
20. If one of the constraint of an equation in an LP problem has an unbounded solution,
    then
    1.   Solution to such LP problem must be degenerate
    2.   Feasible region should have a line segment
    3.   Alternative solutions exist
    4.   None of the above