

McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Bachelor of Computer Applications (BCA) , Bachelor of Management Studies (BMS) .
151. |
The world ‘Linear’ means that the relationships are represented by ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Diagonal lines |
B. | Curved lines |
C. | Straight lines |
D. | Slanting lines |
Answer» C. Straight lines |
152. |
The world ‘ programming’ means taking decisions ‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Systematically |
B. | Rapidly |
C. | Slowly |
D. | Instantly |
Answer» A. Systematically |
153. |
Who originally called it ‘ Programming of interdependent activities in a linear structure’ but later shortened it to ‘ Linear Programming’ ? |
A. | Dantzig |
B. | Kantorovich |
C. | Marshall |
D. | None of the above |
Answer» A. Dantzig |
154. |
LP can be applied in farm management problems is relates to the allocation of resources such as ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ , in such a way that is maximizes net revenue |
A. | Acreage |
B. | Labour |
C. | Water supply or working capital |
D. | All of the above |
Answer» D. All of the above |
155. |
LP model is based on the assumptions of ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Proportionality |
B. | Additivity |
C. | Certainty |
D. | All of the above |
Answer» D. All of the above |
156. |
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ assumption means the prior knowledge of all the coefficients in the objective function, the coefficients of the constraints and the resource values. |
A. | Proportionality |
B. | Certainty |
C. | Finite choices |
D. | Continuity |
Answer» B. Certainty |
157. |
Simple linear programming problem with ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ variables can be easily solved by the graphical method. |
A. | One decision |
B. | Four decisions |
C. | Three decisions |
D. | Two decisions |
Answer» D. Two decisions |
158. |
Any solution to a LPP which satisfies the non‐ negativity restrictions of the LPP is called its ‐‐‐‐‐‐‐‐ |
A. | Unbounded solution |
B. | Optimal solution |
C. | Feasible solution |
D. | Both A and B |
Answer» C. Feasible solution |
159. |
Any feasible solution which optimizes (minimizes or maximizes) the objective function of the LPP is called its ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Optimal solution |
B. | Non‐basic variables |
C. | Solution |
D. | Basic feasible solution |
Answer» A. Optimal solution |
160. |
A non – degenerate basic feasible solution is the basic feasible solution which has exactly m positive Xi (i=1,2,…,m), i.e., none of the basic variable is ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Infinity |
B. | One |
C. | Zero |
D. | X |
Answer» C. Zero |
161. |
What is also defined as the non‐negative variables which are added in the LHS of the constraint to convert the inequality ‘< ‘ into an equation? |
A. | Slack variables |
B. | Simplex algorithm |
C. | Key element |
D. | None of the above |
Answer» A. Slack variables |
162. |
Which method is an iterative procedure for solving LPP in a finite number of steps ? |
A. | Simplex algorithm |
B. | Slack variable |
C. | M method |
D. | Simplex method |
Answer» D. Simplex method |
163. |
In simplex algorithm , which method is used to deal with the situation where an infeasible starting basic solution is given? |
A. | Slack variable |
B. | Simplex method |
C. | M‐ method |
D. | None of the above |
Answer» C. M‐ method |
164. |
How many methods are there to solve LPP? |
A. | Three |
B. | Two |
C. | Four |
D. | None of the above |
Answer» B. Two |
165. |
‐‐‐‐‐‐‐‐‐‐‐‐ is another method to solve a given LPP involving some artificial variable ? |
A. | Big M method |
B. | Method of penalties |
C. | Two‐phase simplex method |
D. | None of the above |
Answer» C. Two‐phase simplex method |
166. |
Which variables are fictitious and cannot have any physical meaning ? |
A. | Optimal variable |
B. | Decision variable |
C. | Artificial variable |
D. | None of the above |
Answer» C. Artificial variable |
167. |
An objective function which states the determinants of the quantity to be either maximized or minimized is called ‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Feasible function |
B. | Optimal function |
C. | Criterion function |
D. | None of the above |
Answer» C. Criterion function |
168. |
An assumption that implies that finite numbers of choices are available to a decision – maker and the decision variables do not assume negative values is known as ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Certainty |
B. | Continuity |
C. | Finite choices |
D. | None of the above |
Answer» C. Finite choices |
169. |
A set of values X1, X2,…Xn which satisfies the constraints of the LPP is called ‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Solution |
B. | Variable |
C. | Linearity |
D. | None of the above |
Answer» A. Solution |
170. |
A basic solution which also satisfies the condition in which all basic variables are non ‐negative is called ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Basic feasible solution |
B. | Feasible solution |
C. | Optimal solution |
D. | None of the above |
Answer» A. Basic feasible solution |
171. |
All the constraints are expressed as equations and the right hand side of each constraint and all variables are non‐negative is called ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Canonical variable |
B. | Canonical form |
C. | Canonical solution |
D. | Both A and B |
Answer» B. Canonical form |
172. |
An objective function is maximized when it is a ‐‐‐‐‐‐‐‐‐‐‐ function |
A. | Passive |
B. | Profit |
C. | Cost |
D. | None of the above |
Answer» B. Profit |
173. |
LPP is exactly used in solving what kind of resource allocation problems? |
A. | Production planning and scheduling |
B. | Transportation |
C. | Sales and advertising |
D. | All of the above |
Answer» D. All of the above |
174. |
Currently, LPP is used in solving a wide range of practical ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Business problems |
B. | Agricultural problems |
C. | Manufacturing problems |
D. | None of the above |
Answer» A. Business problems |
175. |
‐‐‐‐‐‐‐‐‐‐‐‐‐‐ refers to the combination of one or more inputs to produce a particular output. |
A. | Solution |
B. | variable |
C. | Process |
D. | None of the above |
Answer» C. Process |
176. |
An optimum solution is considered the ‐‐‐‐‐‐‐‐‐‐‐‐‐‐ among feasible solutions. |
A. | Worst |
B. | Best |
C. | Ineffective |
D. | None of the above |
Answer» B. Best |
177. |
Please state which statement is true. (i) All linear programming problems may not have unique solutions (ii) The artificial variable technique is not a device that does not get the starting basic feasible solution. |
A. | Both (i) and( ii) |
B. | (ii) only |
C. | (i) only |
D. | Both are incorrect |
Answer» C. (i) only |
178. |
Please state which statement is incorrect. (i) Linear programming was first formulated by an English economist L.V. Kantorovich (ii) LP is generally used in solving maximization or minimization problems subject to certain assumptions. |
A. | (ii) only |
B. | (i) only |
C. | Both (i) and( ii) |
D. | Both are correct |
Answer» B. (i) only |
179. |
‐‐‐‐‐‐‐‐‐‐‐‐ which is a subclass of a linear programming problem (LPP) |
A. | Programming problem |
B. | Transportation problem |
C. | Computer problem |
D. | Both are incorrect |
Answer» B. Transportation problem |
180. |
The solution of any transportation problem is obtained in how many stages? |
A. | Five |
B. | Four |
C. | Three |
D. | Two |
Answer» D. Two |
181. |
An optimal solution is the ‐‐‐‐‐‐‐‐‐‐‐ stage of a solution obtained by improving the initial solution |
A. | Third |
B. | First |
C. | Second |
D. | Final |
Answer» C. Second |
182. |
MODI method is used to obtain ‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Optimal solutions |
B. | Optimality test |
C. | Both A and B |
D. | Optimization |
Answer» C. Both A and B |
183. |
For solving an assignment problem, which method is used? |
A. | Hungarian |
B. | American |
C. | German |
D. | Both are incorrect |
Answer» A. Hungarian |
184. |
To make an unbalanced assignment problem balanced, what are added with all entries as zeroes? |
A. | Dummy rows |
B. | Dummy columns |
C. | Both A and B |
D. | Dummy entries |
Answer» C. Both A and B |
185. |
Any set of non‐negative allocations (Xij>0) which satisfies the raw and column sum (rim requirement )is called a ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Linear programming |
B. | Basic feasible solution |
C. | Feasible solution |
D. | None of the above |
Answer» C. Feasible solution |
186. |
A feasible solution is called a basic feasible solution if the number of non‐negative allocations is equal to ‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | m‐n+1 |
B. | m‐n‐1 |
C. | m+n‐1 |
D. | None of the above |
Answer» C. m+n‐1 |
187. |
Any feasible solution to a transportation problem containing m origins and n destinations is said to be ‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Independent |
B. | Degenerate |
C. | Non‐degenerate |
D. | Both A and B |
Answer» C. Non‐degenerate |
188. |
A path formed by allowing horizontal and vertical lines and the entire corner cells of which are occupied is called a ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Occupied path |
B. | Open path |
C. | Closed path |
D. | None of the above |
Answer» C. Closed path |
189. |
Transportation algorithm can be used for minimizing the transportation cost of ‐‐‐‐‐‐‐‐‐‐‐‐ from O origins and D destinations |
A. | Goods |
B. | Products |
C. | Items |
D. | None of the above |
Answer» A. Goods |
190. |
If demand is lesser than supply then dummy demand node is added to make it a ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Simple problem |
B. | Balanced problem |
C. | Transportation problem |
D. | None of the above |
Answer» B. Balanced problem |
191. |
Basic cells indicate positive values and non‐ basic cells have ‐‐‐‐‐‐‐‐‐‐‐ value for flow |
A. | Negative |
B. | Positive |
C. | One |
D. | zero |
Answer» D. zero |
192. |
According to transportation problem number of basic cells will be exactly ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | m+n‐0 |
B. | n+m‐1 |
C. | m+n‐1 |
D. | None of the above |
Answer» C. m+n‐1 |
193. |
Before starting to solve the problem, it should be balanced. If not then make it balanced by ‐‐‐‐‐ ‐‐‐‐‐‐ column incase demand is less than supply or by adding ‐‐‐‐‐‐‐‐‐‐‐‐ raw incase supply is less than the demand |
A. | O,D |
B. | m,n |
C. | Horizontal, Vertical |
D. | Unshipped supply, Shortage |
Answer» D. Unshipped supply, Shortage |
194. |
In which phase is optimization done and how does that phase also checks for optimality conditions? |
A. | Phase II |
B. | Phase I |
C. | Phase II |
D. | None of the above |
Answer» C. Phase II |
195. |
Optimality conditions are expressed as ‐‐‐‐‐‐‐‐‐‐‐‐‐ incase all non‐basic cells? |
A. | Negligent costs |
B. | Advanced costs |
C. | Reduced costs |
D. | None of the above |
Answer» C. Reduced costs |
196. |
A ‐‐‐‐‐‐‐‐‐ has rows / column having non‐ basic cells for holding compensating (+ )or (‐) sign. |
A. | Cycle |
B. | Dead – end |
C. | Back track |
D. | None of the above |
Answer» A. Cycle |
197. |
After determining every basic cell with in this cycle, adjustment is obtained as minimum value in basic cells . this is known as ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Adjustment amount |
B. | aa |
C. | Both A and B |
D. | Alternatives |
Answer» C. Both A and B |
198. |
Optimal solution is a feasible solution (not necessarily basic ) which minimizes the ‐‐‐‐‐‐‐‐‐‐ |
A. | Time taken |
B. | Partial cost |
C. | Total cost |
D. | None of the above |
Answer» C. Total cost |
199. |
State which of the two statements is correct (i) the cells in the transportation table can be classified in to occupied cells and unoccupied cells (ii) optimal solution is a feasible solution (not necessarily basic ) which maximizes the total cost |
A. | both (i) and (ii) are correct |
B. | Two only |
C. | One only |
D. | Both (i) and (ii) are incorrect |
Answer» C. One only |
200. |
The allocated cells in the transportation table are called ‐‐‐‐‐‐‐‐‐‐‐‐‐ |
A. | Occupied cells |
B. | Empty cells |
C. | Both A and B |
D. | Unoccupied cells |
Answer» A. Occupied cells |
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