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This section includes 657 Mcqs, each offering curated multiple-choice questions to sharpen your Testing Subject knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
In the general linear programming model of the assignment problem, |
| A. | one agent can do parts of several tasks. |
| B. | one task can be done by several agents. |
| C. | each agent is assigned to its own best task. |
| D. | one agent is assigned to one and only one task. |
| Answer» E. | |
| 2. |
Using the transportation simplex method, the optimal solution to the transportation problem has been found when |
| A. | there is a shipment in every cell. |
| B. | more than one stepping-stone path is available. |
| C. | there is a tie for outgoing cell. |
| D. | the net evaluation index for each unoccupied cell is ≥ 0. |
| Answer» E. | |
| 3. |
To find the optimal solution to a linear programming problem using the graphical method |
| A. | find the feasible point that is the farthest away from the origin. |
| B. | find the feasible point that is at the highest location. |
| C. | find the feasible point that is closest to the origin. |
| D. | None of the alternatives is correct. |
| Answer» E. | |
| 4. |
Decision makers in queuing situations attempt to balance |
| A. | operating characteristics against the arrival rate. |
| B. | service levels against service cost. |
| C. | the number of units in the system against the time in the system. |
| D. | the service rate against the arrival rate. |
| Answer» C. the number of units in the system against the time in the system. | |
| 5. |
Non-negativity 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 resources |
| D. | None of the above |
| Answer» E. | |
| 6. |
Identifying the outgoing arc in Phase II of the transportation simplex method is performed using the |
| A. | minimum cost method. |
| B. | MODI method. |
| C. | stepping-stone method. |
| D. | matrix reduction method. |
| Answer» D. matrix reduction method. | |
| 7. |
The amount that the objective function coefficient of a decision variable would have to improve before that variable would have a positive value in the solution is the |
| A. | dual price. |
| B. | surplus variable. |
| C. | reduced cost. |
| D. | upper limit. |
| Answer» D. upper limit. | |
| 8. |
The assignment problem constraint x31 + x32 + x33 + x34 ≤ 2 means |
| A. | agent 3 can be assigned to 2 tasks. |
| B. | agent 2 can be assigned to 3 tasks. |
| C. | a mixture of agents 1, 2, 3, and 4 will be assigned to tasks. |
| D. | there is no feasible solution. |
| Answer» B. agent 2 can be assigned to 3 tasks. | |
| 9. |
In linear programming problem if all constraints are less than or equal to, then the feasible region is |
| A. | Above lines |
| B. | Below the lines |
| C. | Unbounded |
| D. | None of the above |
| Answer» C. Unbounded | |
| 10. |
The per-unit change in the objective function associated with assigning flow to an unused arc in the transportation simplex method is called the |
| A. | net evaluation index. |
| B. | degenerate value. |
| C. | opportunity loss. |
| D. | simplex multiplier. |
| Answer» B. degenerate value. | |
| 11. |
A solution to a transportation problem that has less than m + n − 1 cells with positive allocations in the transportation table is |
| A. | an optimal solution. |
| B. | an initial feasible solution. |
| C. | a minimum-cost solution. |
| D. | a degenerate solution. |
| Answer» E. | |
| 12. |
In the simplex method, a tableau is optimal only if all the cj – zj values are |
| A. | zero or negative. |
| B. | zero. |
| C. | negative and nonzero. |
| D. | positive and nonzero. |
| Answer» B. zero. | |
| 13. |
Which of the following special cases does not require reformulation of the problem in orderto obtain a solution? |
| A. | alternate optimality |
| B. | infeasibility |
| C. | unboundedness |
| D. | each case requires a reformulation. |
| Answer» B. infeasibility | |
| 14. |
Which of the following is not true regarding an LP model of the assignment problem? ] |
| A. | Costs appear in the objective function only. |
| B. | All constraints are of the ≥ form. |
| C. | All constraint left-hand side coefficient values are 1. |
| D. | All decision variable values are either 0 or 1. |
| Answer» C. All constraint left-hand side coefficient values are 1. | |
| 15. |
Which of the following statements is INCORRECT regarding the advantages of simulation? |
| A. | Simulation is relatively easy to explain and understand. |
| B. | Simulation guarantees an optimal solution. |
| C. | Simulation models are flexible. |
| D. | A simulation model provides a convenient experimental laboratory for the real system. |
| Answer» C. Simulation models are flexible. | |
| 16. |
Which of the following is not true regarding the linear programming formulation of a transportation problem? |
| A. | Costs appear only in the objective function. |
| B. | The number of variables is (number of origins) × (number of destinations). |
| C. | The number of constraints is (number of origins) × (number of destinations). |
| D. | The constraints' left-hand side coefficients are either 0 or 1. |
| Answer» D. The constraints' left-hand side coefficients are either 0 or 1. | |
| 17. |
An assignment problem is considered as a particular case of a transportation problem because |
| A. | The number of rows equals columns |
| B. | All xij = 0 or 1 |
| C. | All rim conditions are 1 |
| D. | All of the above |
| Answer» E. | |
| 18. |
The first step in simulation is to |
| A. | set up possible courses of action for testing. |
| B. | construct a numerical model. |
| C. | validate the model. |
| D. | define the problem. |
| Answer» E. | |
| 19. |
An assignment problem is a special case of transportation problem, where |
| A. | Number of rows equals number of columns |
| B. | All rim conditions are 1 |
| C. | Values of each decision variable is either 0 or 1 |
| D. | All of the above |
| Answer» E. | |
| 20. |
When total supply is equal to total demand in a transportation problem, the problem is said to be |
| A. | Balanced |
| B. | Unbalanced |
| C. | Degenerate |
| D. | None of the above |
| Answer» D. None of the above | |
| 21. |
The northwest corner rule requires that we start allocating units to shipping routes in the: |
| A. | middle cell. |
| B. | Lower right corner of the table. |
| C. | Upper right corner of the table. |
| D. | Upper left-hand corner of the table. |
| Answer» E. | |
| 22. |
Maximization assignment problem is transformed into a minimization problem by |
| A. | Adding each entry in a column from the maximization value in that column |
| B. | Subtracting each entry in a column from the maximum value in that column |
| C. | Subtracting each entry in the table from the maximum value in that table |
| D. | Any one of the above |
| Answer» D. Any one of the above | |
| 23. |
The important step required for simulation approach in solving a problem is to |
| A. | Test & validate the model |
| B. | Design the experiment |
| C. | Conduct the experiment |
| D. | All of the above |
| Answer» E. | |
| 24. |
To use the transportation simplex method, a transportation problem that is unbalanced requires the use of |
| A. | artificial variables. |
| B. | one or more transshipment nodes. |
| C. | a dummy origin or destination. |
| D. | matrix reduction. |
| Answer» D. matrix reduction. | |
| 25. |
Decision Science approach is |
| A. | Multi-disciplinary |
| B. | Scientific |
| C. | Intuitive |
| D. | All of the above |
| Answer» B. Scientific | |
| 26. |
An optimal assignment requires that the maximum number of lines that can be drawn through squares with zero opportunity cost be equal to the number of |
| A. | Rows or columns |
| B. | Rows & columns |
| C. | Rows + columns – 1 |
| D. | None of the above |
| Answer» E. | |
| 27. |
The stepping-stone method requires that one or more artificially occupied cells with a flow of zero be created in the transportation tableau when the number of occupied cells is fewer than |
| A. | m + n − 2 |
| B. | m + n − 1 |
| C. | m + n |
| D. | m + n + 1 |
| Answer» C. m + n | |
| 28. |
Decision variables |
| A. | tell how much or how many of something to produce, invest, purchase, hire, etc. |
| B. | represent the values of the constraints. |
| C. | measure the objective function. |
| D. | must exist for each constraint. |
| Answer» B. represent the values of the constraints. | |
| 29. |
The maximization or minimization of a quantity is the |
| A. | goal of management science. |
| B. | decision for decision analysis. |
| C. | constraint of operations research. |
| D. | objective of linear programming. |
| Answer» E. | |
| 30. |
Management science and operations research both involve |
| A. | qualitative managerial skills. |
| B. | quantitative approaches to decision making. |
| C. | operational management skills. |
| D. | scientific research as opposed to applications. |
| Answer» C. operational management skills. | |
| 31. |
A solution that satisfies all the constraints of a linear programming problem except the nonnegativity constraints is called |
| A. | optimal. |
| B. | feasible. |
| C. | infeasible. |
| D. | semi-feasible. |
| Answer» D. semi-feasible. | |
| 32. |
LP theory states that the optimal solution to any problem will lie at |
| A. | the origin. |
| B. | a corner point of the feasible region. |
| C. | the highest point of the feasible region. |
| D. | the lowest point in the feasible region. |
| Answer» C. the highest point of the feasible region. | |
| 33. |
The equally likely decision criterion is also known as |
| A. | Bayes'. |
| B. | Laplace. |
| C. | minimax. |
| D. | Hurwicz. |
| Answer» C. minimax. | |
| 34. |
Which of the following is a valid objective function for a linear programming problem? |
| A. | Max 5xy |
| B. | Min 4x + 3y + (2/3)z |
| C. | Max 5x2+ 6y2 |
| D. | Min (x1 + x2)/x3 |
| Answer» C. Max 5x2+ 6y2 | |
| 35. |
In labor planning formulation, how would you write the constraint that there are only 10 fulltime tellers (labeled as T) available? |
| A. | T + 10 > 0 |
| B. | T > 10 |
| C. | T ≤10 |
| D. | All of the above are correct ways. |
| Answer» D. All of the above are correct ways. | |
| 36. |
Decision alternatives |
| A. | should be identified before decision criteria are established. |
| B. | are limited to quantitative solutions |
| C. | are evaluated as a part of the problem definition stage. |
| D. | are best generated by brain-storming. |
| Answer» B. are limited to quantitative solutions | |
| 37. |
Which of the following is a property of all linear programming problems? |
| A. | alternate courses of action to choose from |
| B. | minimization of some objective |
| C. | a computer program |
| D. | usage of graphs in the solution |
| Answer» B. minimization of some objective | |
| 38. |
A point that satisfies all of a problem's constraints simultaneously is a(n) |
| A. | maximum profit point. |
| B. | corner point. |
| C. | intersection of the profit line and a constraint. |
| D. | None of the above |
| Answer» E. | |
| 39. |
A type of linear programming problem that is used in marketing is called the |
| A. | media selection problem. |
| B. | Madison Avenue problem. |
| C. | marketing allocation problem. |
| D. | all of the above |
| Answer» B. Madison Avenue problem. | |
| 40. |
Which of the following might be viewed as an "optimistic" decision criterion? |
| A. | Hurwicz criterion |
| B. | Maximin |
| C. | Maximax |
| D. | Minimax |
| Answer» D. Minimax | |
| 41. |
All of the following are steps in the decision-making process EXCEPT: |
| A. | Define the problem |
| B. | Compute the posterior probabilities |
| C. | Identify possible outcomes |
| D. | List payoffs |
| Answer» C. Identify possible outcomes | |
| 42. |
The first step in formulating an LP problem is |
| A. | Graph the problem. |
| B. | Understand the managerial problem being faced. |
| C. | Identify the objective and the constraints. |
| D. | Define the decision variables. |
| Answer» C. Identify the objective and the constraints. | |
| 43. |
In converting a less-than-or-equal constraint for use in a simplex table, we must add |
| A. | a surplus variable. |
| B. | a slack variable. |
| C. | an artificial variable. |
| D. | both a surplus and a slack variable. |
| Answer» C. an artificial variable. | |
| 44. |
Consider the following linear programming problem: |
| A. | (40,48) |
| B. | (120,0) |
| C. | (180,120) |
| D. | (30,36) |
| Answer» C. (180,120) | |
| 45. |
Which of the following does not represent a factor a manager might consider when employing linear programming for a production scheduling? |
| A. | labor capacity |
| B. | employee skill levels |
| C. | warehouse limitations |
| D. | none of the above |
| Answer» E. | |
| 46. |
A good decision always implies that we |
| A. | will obtain the best final results |
| B. | have used appropriate quantitative analysis. |
| C. | have followed a logical process. |
| D. | have based the decision on all available appropriate information. |
| Answer» D. have based the decision on all available appropriate information. | |
| 47. |
The quantitative analysis approach requires |
| A. | the manager's prior experience with a similar problem. |
| B. | a relatively uncomplicated problem. |
| C. | mathematical expressions for the relationships. |
| D. | each of the above is true. |
| Answer» D. each of the above is true. | |
| 48. |
Slack |
| A. | Is the difference between the left and right sides of a constraint. |
| B. | Is the amount by which the left side of a ≤ constraint is smaller than the right side. |
| C. | Is the amount by which the left side of a ≥ constraint is larger than the right side. |
| D. | Exists for each variable in a linear programming problem. |
| Answer» C. Is the amount by which the left side of a ≥ constraint is larger than the right side. | |