Operations Research Set 5
On This Page
This set of Operations Research Multiple Choice Questions & Answers (MCQs) focuses on Operations Research Set 5
Q1 | ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ are the representation of reality
- Models
- Phases
- Both A and B
- None of the above
Q2 | ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ are called mathematical models
- Iconic Models
- Analogue Models
- Symbolic Models
- None of the above
Q3 | It is not easy to make any modification or improvement in
- Iconic Models
- Analogue Models
- Symbolic Models
- None of the above
Q4 | In ‐‐‐‐‐‐‐‐‐‐ models one set of properties is used to represent another set of properties
- Iconic Models
- Analogue Models
- Symbolic Models
- None of the above
Q5 | Allocation Models are ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
- Iconic models
- Analogue Models
- Symbolic Models
- None of the above
Q6 | Probabilistic models are also known as
- Deterministic Models
- Stochastic Models
- Dynamic Models
- Static Models
Q7 | ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ models assumes that the values of the variables do not change with time during aparticular period
- Static Models
- Dynamic Models
- Both A and B
- None of the above
Q8 | A ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ models considers time as one of the important variable
- Static Models
- Dynamic Models
- Both A and B
- None of the above
Q9 | Replacement Model is a ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ model
- Static Models
- Dynamic Models
- Both A and B
- None of the above
Q10 | ‐‐‐‐‐‐‐‐‐‐‐‐‐‐ may be defined as a method of determining an optimum programme interdependent activities in view of available resources
- Goal Programming
- Linear Programming
- Decision Making
- None of the above
Q11 | ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ are expressed is n the form of inequities or equations
- Constraints
- Objective Functions
- Both A and B
- None of the above
Q12 | The objective functions and constraints are linear relationship between ‐‐‐‐‐‐‐‐‐‐‐‐‐
- Variables
- Constraints
- Functions
- All of the above
Q13 | Assignment problem helps to find a maximum weight identical in nature in a weighted ‐‐‐‐‐‐‐‐‐‐‐‐
- Tripartite graph
- Bipartite graph
- Partite graph
- None of the above
Q14 | All the parameters in the linear programming model are assumed to be ‐‐‐‐‐‐‐‐‐‐‐‐
- Variables
- Constraints
- Functions
- None of the above
Q15 | The solution need not be in ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ numbers
- Prime Number
- Whole Number
- Complex Number
- None of the above
Q16 | Graphic method can be applied to solve a LPP when there are only ‐‐‐‐‐‐‐‐‐‐‐‐‐ variable
- One
- More than One
- Two
- Three
Q17 | If the feasible region of a LPP is empty, the solution is ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
- Infeasible
- Unbounded
- Alternative
- None of the above
Q18 | The variables whose coefficient vectors are unit vectors are called ‐‐‐‐‐‐‐‐‐‐‐‐
- Unit Variables
- Basic Variables
- Non basic Variables
- None of the above
Q19 | Any column or raw of a simplex table is called a ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
- Vector
- Key column
- Key Raw
- None of the above
Q20 | A minimization problem can be converted into a maximization problem by changing the sign ofcoefficients in the ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
- Constraints
- Objective Functions
- Both A and B
- None of the above
Q21 | If in a LPP , the solution of a variable can be made infinity large without violating the constraints,the solution is ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
- Infeasible
- Unbounded
- Alternative
- None of the above
Q22 | In maximization cases , ‐‐‐‐‐‐‐‐‐‐‐‐‐ are assigned to the artificial variables as their coefficients inthe objective function
- +m
- –m
- None of the above
Q23 | In simplex method , we add ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ variables in the case of ‘=’
- Slack Variable
- Surplus Variable
- Artificial Variable
- None of the above
Q24 | In simplex method, if there is tie between a decision variable and a slack (or surplus) variable, ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ should be selected
- Slack variable
- Surplus variable
- Decision variable
- None of the above
Q25 | A BFS of a LPP is said to be ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ if at least one of the basic variable is zero
- Degenerate
- Non‐degenerate
- Infeasible
- Unbounded