McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Uncategorized topics .
| 151. |
A feasible solution to a linear programming problem |
| A. | Must satisfy all problem constraints simultaneously |
| B. | Need not satisfy all constraints |
| C. | Must be a corner point of the feasible region |
| D. | Must optimize the value of the objective function |
| Answer» A. Must satisfy all problem constraints simultaneously | |
| 152. |
While plotting constraints on a graph paper, terminal points on both axes are connected by a straight line because |
| A. | The resources are limited in supply |
| B. | The objective function is a linear function |
| C. | The constraints are linear equations or in equalities |
| D. | all of the above |
| Answer» C. The constraints are linear equations or in equalities | |
| 153. |
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 of (a) and (b) |
| D. | None of the above |
| Answer» A. Represent optimal solution | |
| 154. |
The solution space of a LP problem is unbounded due to |
| A. | An incorrect formulation of the LP model |
| B. | Objective function is unbounded |
| C. | Neither (a) nor (b) |
| D. | Both (a) and (b) |
| Answer» C. Neither (a) nor (b) | |
| 155. |
The graphical method of LP problem uses |
| A. | Objective function equation |
| B. | Constraint equation |
| C. | Linear equations |
| D. | All the above |
| Answer» D. All the above | |
| 156. |
While solving LP problem graphically, the area bounded by the constraints is called |
| A. | Feasible region |
| B. | Infeasible region |
| C. | Unbounded solution |
| D. | None of the above |
| Answer» A. Feasible region | |
| 157. |
Which of the following is not a category of linear programming problems? |
| A. | Resource allocation problem |
| B. | Cost benefit trade off problem |
| C. | Distribution network problem |
| D. | All of the above are categories of linear programming problems. |
| Answer» D. All of the above are categories of linear programming problems. | |
| 158. |
Which of the following may not be in a linear programming formulation? |
| A. | <=. |
| B. | >. |
| C. | =. |
| D. | All the above |
| Answer» B. >. | |
| 159. |
While solving an LP problem infeasibility may be removed by |
| A. | Adding another constraint |
| B. | Adding another variable |
| C. | Removing a constraint |
| D. | Removing a variable |
| Answer» C. Removing a constraint | |
| 160. |
A linear programming model does not contain which of the following components? |
| A. | Data |
| B. | Decisions |
| C. | Constraints |
| D. | A spread sheet |
| Answer» D. A spread sheet | |
| 161. |
Straight lines shown in a linear programming graph indicates |
| A. | Objective function |
| B. | Constraints |
| C. | Points |
| D. | All the above |
| Answer» B. Constraints | |
| 162. |
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» B. Below the lines | |
| 163. |
……. is a series of related activities which result in some product or services. |
| A. | Network |
| B. | transportation model |
| C. | assignment |
| D. | none of these |
| Answer» A. Network | |
| 164. |
Any activity which does not consume either any resource or time is called ………..activity. |
| A. | Predecessor |
| B. | Successor |
| C. | Dummy |
| D. | End |
| Answer» C. Dummy | |
| 165. |
All negative constraints must be written as |
| A. | Equality |
| B. | Non equality |
| C. | Greater than or equal to |
| D. | Less than or equal to |
| Answer» C. Greater than or equal to | |
| 166. |
Activities that cannot be started until one or more of the other activities are completed, but immediately succeed them are called ……activities |
| A. | Predecessor |
| B. | Successor |
| C. | Dummy |
| D. | End |
| Answer» B. Successor | |
| 167. |
An event which represents the beginning of more than one activity is known as ………..event. |
| A. | Merge |
| B. | Net |
| C. | Burst |
| D. | None of the above |
| Answer» C. Burst | |
| 168. |
If two constraints do not intersect in the positive quadrant of the graph, then |
| A. | The problem is infeasible |
| B. | The solution is unbounded |
| C. | One of the constraints is redundant |
| D. | None of the above |
| Answer» D. None of the above | |
| 169. |
An activity which must be completed before one or more other activities start is known as ……….activity. |
| A. | Predecessor |
| B. | Successor |
| C. | Dummy |
| D. | End |
| Answer» A. Predecessor | |
| 170. |
Constraint in LP problem are called active if they |
| A. | Represent optimal solution |
| B. | At optimality do not consume all the available resources |
| C. | Both of (a) and (b) |
| D. | None of the above |
| Answer» A. Represent optimal solution | |
| 171. |
While solving an LP problem, infeasibility may be removed by |
| A. | Adding another constraint |
| B. | Adding another variable |
| C. | Removing a constraint |
| D. | Removing a variable |
| Answer» C. Removing a constraint | |
| 172. |
….……..is that sequence of activities which determines the total project time. |
| A. | Net work |
| B. | Critical path |
| C. | Critical activities |
| D. | None of the above |
| Answer» B. Critical path | |
| 173. |
Activities lying on the critical path are called…………. |
| A. | Net work |
| B. | Critical path |
| C. | Critical activities |
| D. | None of the above |
| Answer» C. Critical activities | |
| 174. |
………..models in which the input and output variables follow a probability distribution. |
| A. | Iconic |
| B. | mathematical |
| C. | analogue |
| D. | Deterministic model |
| Answer» D. Deterministic model | |
| 175. |
………. Example of probabilistic model |
| A. | Game theory |
| B. | Charts |
| C. | Graphs |
| D. | All the above |
| Answer» A. Game theory | |
| 176. |
Alternative solutions exists of an LP model when |
| A. | One of the constraints is redundant. |
| B. | Objective function equation is parallel to one of the constraints |
| C. | Two constraints are parallel. |
| D. | all of the above |
| Answer» B. Objective function equation is parallel to one of the constraints | |
| 177. |
. ………..is a method of analyzing the current movement of the same variable in an effort to predict the future movement of the same variable. |
| A. | Goal programming |
| B. | Markov analysis |
| C. | Replacement theory |
| D. | Queuing theory |
| Answer» B. Markov analysis | |
| 178. |
Decision Science approach is |
| A. | Multi-disciplinary |
| B. | Scientific |
| C. | Intuitive |
| D. | All of the above |
| Answer» A. Multi-disciplinary | |
| 179. |
For analyzing a problem, decision-makers should study |
| A. | Its qualitative aspects |
| B. | Its quantitative aspects |
| C. | Both a & b |
| D. | Neither a nor b |
| Answer» C. Both a & b | |
| 180. |
Decision variables are |
| A. | Controllable |
| B. | Uncontrollable |
| C. | Parameters |
| D. | None of the above |
| Answer» A. Controllable | |
| 181. |
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 | |
| 182. |
Managerial decisions are based on |
| A. | An evaluation of quantitative data |
| B. | The use of qualitative factors |
| C. | Results generated by formal models |
| D. | All of the above |
| Answer» D. All of the above | |
| 183. |
The use of decision models |
| A. | Is possible when the variables value is known |
| B. | Reduces the scope of judgement & intuition known with certainty in decision-making |
| C. | Require the use of computer software |
| D. | None of the above |
| Answer» D. None of the above | |
| 184. |
Every mathematical model |
| A. | Must be deterministic |
| B. | Requires computer aid for its solution |
| C. | Represents data in numerical form |
| D. | All of the above |
| Answer» C. Represents data in numerical form | |
| 185. |
A physical model is example of |
| A. | An iconic model |
| B. | An analogue model |
| C. | A verbal model |
| D. | A mathematical model |
| Answer» C. A verbal model | |
| 186. |
An optimization model |
| A. | Provides the best decision |
| B. | Provides decision within its limited context |
| C. | Helps in evaluating various alternatives |
| D. | All of the above |
| Answer» A. Provides the best decision | |
| 187. |
The quantitative approach to decision analysis is a |
| A. | Logical approach |
| B. | Rational approach |
| C. | Scientific approach |
| D. | All of the above |
| Answer» C. Scientific approach | |
| 188. |
The qualitative approach to decision analysis relies on |
| A. | Experience |
| B. | Judgement |
| C. | Intuition |
| D. | All of the above |
| Answer» D. All of the above | |
| 189. |
The mathematical model of an LP problem is important because |
| A. | It helps in converting the verbal description & 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 technique |
| Answer» A. It helps in converting the verbal description & numerical data into mathematical expression | |
| 190. |
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 | |
| 191. |
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 | |
| 192. |
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 | |
| 193. |
Constraints in an LP model represents |
| A. | Limitations |
| B. | Requirements |
| C. | Balancing limitations & requirements |
| D. | All of the above |
| Answer» D. All of the above | |
| 194. |
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 | |
| 195. |
Before formulating a formal LP model, it is better to |
| A. | Express each constrain 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 | |
| 196. |
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» A. Value occurs at allowable set of decisions | |
| 197. |
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» B. An objective function of maximization type | |
| 198. |
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» D. All of the above | |
| 199. |
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 | |
| 200. |
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» D. None of the above | |
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