Decision Science | Chapter 2 | Part 4 | MBA MCQs | DS

Decision Science MCQs

  

 

1. Simulation
   1.   does not guarantee optimality.
   2.   All of the alternatives are correct.
   3.   allows testing of the system without affecting the real system.
   4.   is flexible and does not require the assumptions of theoretical models.
2. A simulation model used in situations where the state of the system at one point in time
   does not affect the state of the system at future points in time is called a
   1.   dynamic simulation model.
   2.   static simulation model.
   3.   steady-state simulation model.
   4.   discrete-event simulation model.
3. When events occur at discrete points in time
   1.   a simulation clock is required.
   2.   All of the alternatives are correct
   3.   the model is a discrete-event simulation.
   4.   the simulation advances to the next event
4. The process of determining that the computer procedure that performs the simulation calculations is logically correct is called
   1.   repetition.
   2.   verification.
   3.   validation.
   4.   implementation.
5. Numerical values that appear in the mathematical relationships of a model and are
   considered known and remain constant over all trials of a simulation are
   1.   parameters.
   2.   probabilistic input
   3.   controllable input.
   4.   events.
6. The word "uniform" in the term "uniform random numbers" means
   1.   all the numbers have the same number of digits.
   2.   all the numbers are odd or all are even
   3.   each number has an equal probability of being drawn.
   4.   if one number is, say, 10 units above the mean, the next number will be 10 units
      below the mean.
7. The first step in simulation is to
   1.   set up possible courses of action for testing.
   2.   validate the model.
   3.   construct a numerical model
   4.   define the problem.
8. Which of the following are disadvantages of simulation?
   1.   inability to analyze large and complex real-world situations
   2.   is not usually easily transferable to other problems
   3.   could be disruptive by interfering with the real-world system
   4.   "time compression" capability
9. Cumulative probabilities are found by
   1.   summing all the probabilities associated with a variable.
   2.   any method one chooses.
   3.   summing all the previous probabilities up to the current value of the variable.
   4.   simulating the initial probability distribution.
10. Which of the following statements is INCORRECT regarding the advantages of simulation?
    1.   Simulation is relatively easy to explain and understand.
    2.   Simulation models are flexible.
    3.   A simulation model provides a convenient experimental laboratory for the real
       system.
    4.   Simulation guarantees an optimal solution.
11. If we are going to simulate an inventory problem, we must
    1.   Run the simulation for many days.
    2.   Run the simulation many times, i.e., using multiple sets of random numbers.
    3.   Run the simulation once, for a relative short period of time
    4.   Run the simulation for many days many times, i.e., using multiple sets of random
       numbers
12. Simulation should be thought of as a technique for
    1.   obtaining a relatively inexpensive solution to a problem.
    2.   increasing one's understanding of a problem.
    3.   providing quick and dirty answers to complex problems
    4.   obtaining an optimal solution to a problem.
13. In assigning random numbers in a Monte Carlo simulation, it is important to ________.
    1.   develop cumulative probability distributions
    2.   use Excel spreadsheets
    3.   use random numbers from a random number table
    4.   use only a single set of random numbers
14. To simulate is to try to __________ the features, appearance, and characteristics of a
    real system.
    1.   Develop
    2.   Duplicate
    3.   Multiply
    4.   Analyze
15. The three types of mathematical simulation models are
    
    1.   operational gaming, Monte Carlo, systems simulation
    2.   Monte Carlo, queuing, maintenance policy
    3.   system simulation, operational gaming, weather forecasting
    4.   Monte Carlo, systems simulation, computer gaming.
16. Which of the following as an assumption of an LP model
    1.   Divisibility
    2.   all of the above
    3.   Additively
    4.   Proportionality
17. Most of the constraints in the linear programming problem are expressed as ……….
    1.   Equality
    2.   Inequality
    3.   Uncertain
    4.   all of the above
18. A feasible solution to a linear programming problem
    1.   Must optimize the value of the objective function
    2.   Need not satisfy all constraints
    3.   Must be a corner point of the feasible region
    4.   Must satisfy all problem constraints simultaneously
19. While plotting constraints on a graph paper, terminal points on both axes are connected
    by a straight line because
    1.   The resources are limited in supply
    2.   all of the above
    3.   The constraints are linear equations or in equalities
    4.   The objective function is a linear function
20. Constraints in LP problem are called active if they
    1.   Represent optimal solution
    2.   Both of (a) and (b)
    3.   None of the above
    4.   At optimality do not consume all the available resources