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
✅ The correct answer is option D.
The relationship among decision variables in linear,
No guarantee to get integer valued solutions and
No consideration of effect of time & uncertainty on LP model are the limitation associated with an LP model.

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
✅ The correct answer is option D.
The important step required for simulation approach in solving a problem is to Test & validate the model, Design the experiment and conduct the experiment.

A problem is classified as Markov chain provided.

A. There are finite number of possible states
B. States are collectively exhaustive & mutually exclusive
C. Long-run probabilities of being in a particular state will be constant over time
D. All of the above
✅ The correct answer is option D.
A problem is classified as Markov chain provided are there are finite number of possible states, States are collectively exhaustive & mutually exclusive and Long-run probabilities of being in a particular state will be constant over time.

What refers to Linear Programming that includes an evaluation of relative risks and uncertainties in various alternatives of choice for management decisions ?

A. Probabilistic Programming
B. Stochastic Programming
C. Both A and B
D. Linear Programming
✅ The correct answer is option C.
Probabilistic Programming and Stochastic Programming refers to Linear Programming that includes an evaluation of relative risks and uncertainties in various alternatives of choice for management decisions. Probabilistic programming is a programming paradigm in which probabilistic models are specified and inference for these models is performed automatically. Stochastic Programming. Stochastic programs are mathematical programs where some of the data incorporated into the objective or constraints is uncertain.

If the feasible region of a LPP is empty, the solution is ______________.

A. Infeasible
B. Unbounded
C. Alternative
D. None of the above
✅ The correct answer is option A.
If the feasible region of a LPP is empty, the solution is infeasible. A linear program is infeasible if there exists no solution that satisfies all of the constraints — in other words, if no feasible solution can be constructed. Since any real operation that you are modelling must remain within the constraints of reality, infeasibility most often indicates an error of some kind. Simplex-based LP software like lp_solve efficiently detects when no feasible solution is possible.

In simplex method, we add _____________ variables in the case of ‘=’.

A. Slack Variable
B. Surplus Variable
C. Artificial Variable
D. None of the above
✅ The correct answer is option C.
In simplex method, we add artificial variable variables in the case of ‘=’. In order to use the simplex method on problems with mixed constraints, we turn to a device called an artificial variable. This variable has no physical meaning in the original problem and is introduced solely for the purpose of obtaining a basic feasible solution so that we can apply the simplex method.

Biased random sampling is made from among alternatives which have.

A. Equal probability
B. Unequal probability
C. Probability which do not sum to 1
D. None of the above
✅ The correct answer is option B.
Biased random sampling is made from among alternatives which have Unequal probability. A sampling method is called biased if it systematically favors some outcomes over others.

Markov analysis is useful for:

A. Predicting the state of the system at some future time
B. Calculating transition probabilities at some future time
C. All of the above
D. None of the above
✅ The correct answer is option C.
Markov analysis is useful for Predicting the state of the system at some future time and Calculating transition probabilities at some future time.

What have been constructed for Operations Research problems and methods for solving the models that are available in many cases?

A. Scientific Models
B. Algorithms
C. Mathematical Models
D. None of the above
✅ The correct answer is option C.
Mathematical Models have been constructed for Operations Research problems and methods for solving the models that are available in many cases. A mathematical model can be defined as a description of a system using mathematical concepts and language to facilitate proper explanation of a system or to study the effects of different components and to make predictions on patterns of behaviour (Abramowitz and Stegun, 1968).