McqMate
Chapters
1. |
Operation research approach is |
A. | multi-disciplinary |
B. | artificial |
C. | intuitive |
D. | all of the above |
Answer» D. all of the above |
2. |
Operation research analysis does not |
A. | predict future operation |
B. | build more than one model |
C. | collect the relevant data |
D. | recommended decision and accept |
Answer» A. predict future operation |
3. |
A constraint in an LP model restricts |
A. | value of the objective function |
B. | value of the decision variable |
C. | use of the available resourses |
D. | all of the above |
Answer» D. all of the above |
4. |
A feasible solution of LPP |
A. | must satisfy all the constraints simultaneously |
B. | need not satisfy all the constraints, only some of them |
C. | must be a corner point of the feasible region |
D. | all of the above |
Answer» A. must satisfy all the constraints simultaneously |
5. |
Maximization of objective function in LPP means |
A. | value occurs at allowable set decision |
B. | highest value is chosen among allowable decision |
C. | none of the above |
D. | all of the above |
Answer» B. highest value is chosen among allowable decision |
6. |
Alternative solution exist in a linear programming problem when |
A. | one of the constraint is redundant |
B. | objective function is parallel to one of the constraints |
C. | two constraints are parallel |
D. | all of the above |
Answer» D. all of the above |
7. |
The linear function of the variables which is to be maximize or minimize is called |
A. | constraints |
B. | objective function |
C. | decision variable |
D. | none of the above |
Answer» B. objective function |
8. |
The true statement for the graph of inequations 3x+2y≤6 and 6x+4y≥20 , is |
A. | both graphs are disjoint |
B. | both do not contain origin |
C. | both contain point (1, 1) |
D. | none of these |
Answer» A. both graphs are disjoint |
9. |
The value of objective function is maximum under linear constraints |
A. | at the center of feasible region |
B. | at (0,0) |
C. | at any vertex of feasible region |
D. | the vertex which is at maximum distance from (0, 0) |
Answer» C. at any vertex of feasible region |
10. |
A model is |
A. | an essence of reality |
B. | an approximation |
C. | an idealization |
D. | all of the above |
Answer» D. all of the above |
11. |
The first step in formulating a linear programming problem is |
A. | identify any upper or lower bound on the decision variables |
B. | state the constraints as linear combinations of the decision variables |
C. | understand the problem |
D. | identify the decision variables |
Answer» D. identify the decision variables |
12. |
Constraints in an LP model represents |
A. | limititations |
B. | requirements |
C. | balancing, limitations and requirements |
D. | all of above |
Answer» D. all of above |
13. |
The best use of linear programming is to find optimal use of |
A. | money |
B. | manpower |
C. | machine |
D. | all the above |
Answer» D. all the above |
14. |
Which of the following is assumption of an LP model |
A. | divisibility |
B. | proportionality |
C. | additivity |
D. | all of the above |
Answer» D. all of the above |
15. |
Before formulating a formal LP model, it is better to |
A. | express each constraints in words |
B. | express the objective function in words |
C. | verbally identify decision variables |
D. | all of the above |
Answer» D. all of the above |
16. |
Non-negative condition in an LP model implies |
A. | a positive coefficient of variables in objective function |
B. | a positive coefficient of variables in any constraint |
C. | non-negative value of resourse |
D. | none of the above |
Answer» C. non-negative value of resourse |
17. |
The set of decision variable which satisfies all the constraints of the LPP is called as----- |
A. | solution |
B. | basic solution |
C. | feasible solution |
D. | none of the above |
Answer» A. solution |
18. |
The intermediate solutions of constraints must be checked by substituting them back into |
A. | objective function |
B. | constraint equations |
C. | not required |
D. | none of the above |
Answer» B. constraint equations |
19. |
A basic solution is called non-degenerate, if |
A. | all the basic variables are zero |
B. | none of the basic variables is zero |
C. | at least one of the basic variables is zero |
D. | none of these |
Answer» B. none of the basic variables is zero |
20. |
The graph of x≤2 and y≥2 will be situated in the |
A. | first and second quadrant |
B. | second and third quadrant |
C. | first and third quadrant |
D. | third and fourth quadrant |
Answer» B. second and third quadrant |
21. |
A solution which satisfies non-negative conditions also is called as----- |
A. | solution |
B. | basic solution |
C. | feasible solution |
D. | none of the above |
Answer» C. feasible solution |
22. |
A solution which optimizes the objective function is called as ------ |
A. | solution |
B. | basic solution |
C. | feasible solution |
D. | optimal solution |
Answer» D. optimal solution |
23. |
In. L.P.P---- |
A. | objective function is linear |
B. | constraints are linear |
C. | both objective function and constraints are linear |
D. | none of the above |
Answer» C. both objective function and constraints are linear |
24. |
If the constraints in a linear programming problem are changed |
A. | the problem is to be re-evaluated |
B. | solution is not defined |
C. | the objective function has to be modified |
D. | the change in constraints is ignored. |
Answer» A. the problem is to be re-evaluated |
25. |
Linear programming is a |
A. | constrained optimization technique |
B. | technique for economic allocation of limited resources |
C. | mathematical technique |
D. | all of the above |
Answer» D. all of the above |
26. |
A constraint in an LP model restricts |
A. | value of objective function |
B. | value of a decision variable |
C. | use of the available resources |
D. | all of the above |
Answer» D. all of the above |
27. |
The distinguishing feature of an LP model is |
A. | relationship among all variables is linear |
B. | it has single objective function & constraints |
C. | value of decision variables is non-negative |
D. | all of the above |
Answer» A. relationship among all variables is linear |
28. |
The best use of linear programming technique is to find an optimal use of |
A. | money |
B. | manpower |
C. | machine |
D. | all of the above |
Answer» B. manpower |
29. |
Which of the following is not a characteristic of the LP |
A. | resources must be limited |
B. | only one objective function |
C. | parameters value remains constant during the planning period |
D. | the problem must be of minimization type |
Answer» D. the problem must be of minimization type |
30. |
Which of the following is an assumption of an LP model |
A. | divisibility |
B. | proportionality |
C. | additivity |
D. | all of the above |
Answer» D. all of the above |
31. |
Which of the following is a limitation associated with an LP model |
A. | the relationship among decision variables in linear |
B. | no guarantee to get integer valued solutions |
C. | no consideration of effect of time & uncertainty on lp model |
D. | all of the above |
Answer» D. all of the above |
32. |
The graphical method of LP problem uses |
A. | objective function equation |
B. | constraint equations |
C. | linear equations |
D. | all of the above |
Answer» D. all of the above |
33. |
A feasible solution to an LP problem |
A. | must satisfy all of the problem’s constraints simultaneously |
B. | need not satisfy all of the constraints, only some of them |
C. | must be a corner point of the feasible region |
D. | must optimize the value of the objective function |
Answer» D. must optimize the value of the objective function |
34. |
An iso-profit line represents |
A. | an infinite number of solutions all of which yield the same profit |
B. | an infinite number of solution all of which yield the same cost |
C. | an infinite number of optimal solutions |
D. | a boundary of the feasible region |
Answer» D. a boundary of the feasible region |
35. |
If an iso-profit line yielding the optimal solution coincides with a constaint line, then |
A. | the solution is unbounded |
B. | the solution is infeasible |
C. | the constraint which coincides is redundant |
D. | none of the above |
Answer» A. the solution is unbounded |
36. |
A constraint in an LP model becomes redundant because |
A. | two iso-profit line may be parallel to each other |
B. | the solution is unbounded |
C. | this constraint is not satisfied by the solution values |
D. | none of the above |
Answer» A. two iso-profit line may be parallel to each other |
37. |
Constraints in LP problem are called active if they |
A. | represent optimal solution |
B. | at optimality do not consume all the available resources |
C. | both a & b |
D. | none of the above |
Answer» A. represent optimal solution |
38. |
Mathematical model of Linear Programming is important because |
A. | It helps in converting the verbal description and numerical data into mathematical expression |
B. | decision makers prefer to work with formal models. |
C. | it captures the relevant relationship among decision factors. |
D. | it enables the use of algebraic techniques. |
Answer» A. It helps in converting the verbal description and numerical data into mathematical expression |
39. |
In graphical method of linear programming problem if the iOS-cost line coincide with a side of region of basic feasible solutions we get |
A. | Unique optimum solution |
B. | unbounded optimum solution |
C. | no feasible solution |
D. | Infinite number of optimum solutions |
Answer» D. Infinite number of optimum solutions |
40. |
If the value of the objective function 𝒛 can be increased or decreased indefinitely, such solution is called |
A. | Bounded solution |
B. | Unbounded solution |
C. | Solution |
D. | None of the above |
Answer» B. Unbounded solution |
41. |
For the constraint of a linear optimizing function z=x1+x2 given by x1+x2≤1, 3x1+x2≥3 and x1, x2≥0 |
A. | There are two feasible regions |
B. | There are infinite feasible regions |
C. | There is no feasible region |
D. | None of these |
Answer» C. There is no feasible region |
42. |
If the number of available constraints is 3 and the number of parameters to be optimized is 4, then |
A. | The objective function can be optimized |
B. | The constraints are short in number |
C. | The solution is problem oriented |
D. | None of these |
Answer» B. The constraints are short in number |
43. |
Non-negativity condition is an important component of LP model because |
A. | Variables value should remain under the control of the decision-maker |
B. | Value of variables make sense & correspond to real-world problems |
C. | Variables are interrelated in terms of limited resources |
D. | None of the above |
Answer» B. Value of variables make sense & correspond to real-world problems |
44. |
Maximization of objective function in an LP model means |
A. | Value occurs at allowable set of decisions |
B. | Highest value is chosen among allowable decisions |
C. | Neither of above |
D. | Both a & b |
Answer» D. Both a & b |
45. |
Which of the following is not a characteristic of the LP model |
A. | Alternative courses of action |
B. | An objective function of maximization type |
C. | Limited amount of resources |
D. | Non-negativity condition on the value of decision variables. |
Answer» A. Alternative courses of action |
46. |
Which of the following statements is true with respect to the optimal solution of an LP problem |
A. | Every LP problem has an optimal solution |
B. | Optimal solution of an LP problem always occurs at an extreme point |
C. | At optimal solution all resources are completely used |
D. | If an optimal solution exists, there will always be at least one at a corner |
Answer» A. Every LP problem has an optimal solution |
47. |
While plotting constraints on a graph paper, terminal points on both the axes are connected by a straight line because |
A. | The resources are limited in supply |
B. | The objective function as a linear function |
C. | The constraints are linear equations or inequalities |
D. | All of the above |
Answer» D. All of the above |
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