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

Decision Science MCQs

  

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1. The first step in simulation is to
   1.   construct a numerical model
   2.   validate the model.
   3.   set up possible courses of action for testing.
   4.   define the problem.
2. A feasible solution to a linear programming problem
   1.   Must optimize the value of the objective function
   2.   Must satisfy all problem constraints simultaneously
   3.   Must be a corner point of the feasible region
   4.   Need not satisfy all constraints
3. 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.   controllable input.
   2.   parameters.
   3.   events.
   4.   probabilistic input
4. The word "uniform" in the term "uniform random numbers" means
   1.   each number has an equal probability of being drawn.
   2.   all the numbers are odd or all are even
   3.   all the numbers have the same number of digits.
   4.   if one number is, say, 10 units above the mean, the next number will be 10 units
      below the mean.
5. To simulate is to try to __________ the features, appearance, and characteristics of a
   real system.
   1.   Develop
   2.   Duplicate
   3.   Analyze
   4.   Multiply
6. The process of determining that the computer procedure that performs the simulation calculations is logically correct is called
   1.   implementation.
   2.   validation.
   3.   verification.
   4.   repetition.
7. In assigning random numbers in a Monte Carlo simulation, it is important to ________.
   1.   develop cumulative probability distributions
   2.   use random numbers from a random number table
   3.   use only a single set of random numbers
   4.   use Excel spreadsheets
8. Most of the constraints in the linear programming problem are expressed as ……….
   1.   Inequality
   2.   all of the above
   3.   Uncertain
   4.   Equality
9. Which of the following are disadvantages of simulation?
   1.   is not usually easily transferable to other problems
   2.   "time compression" capability
   3.   could be disruptive by interfering with the real-world system
   4.   inability to analyze large and complex real-world situations
10. Constraints in LP problem are called active if they
    1.   At optimality do not consume all the available resources
    2.   Both of (a) and (b)
    3.   None of the above
    4.   Represent optimal solution
11. 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.   steady-state simulation model.
    2.   static simulation model.
    3.   discrete-event simulation model.
    4.   dynamic simulation model.
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. 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 for many days many times, i.e., using multiple sets of random
       numbers
    4.   Run the simulation once, for a relative short period of time
14. Cumulative probabilities are found by
    1.   simulating the initial probability distribution.
    2.   summing all the probabilities associated with a variable.
    3.   summing all the previous probabilities up to the current value of the variable.
    4.   any method one chooses.
15. While plotting constraints on a graph paper, terminal points on both axes are connected
    by a straight line because
    1.   all of the above
    2.   The objective function is a linear function
    3.   The constraints are linear equations or in equalities
    4.   The resources are limited in supply
16. Which of the following statements is INCORRECT regarding the advantages of simulation?
    1.   A simulation model provides a convenient experimental laboratory for the real
       system.
    2.   Simulation guarantees an optimal solution.
    3.   Simulation models are flexible.
    4.   Simulation is relatively easy to explain and understand.
17. When events occur at discrete points in time
    1.   the model is a discrete-event simulation.
    2.   the simulation advances to the next event
    3.   All of the alternatives are correct
    4.   a simulation clock is required.
18. The three types of mathematical simulation models are
    
    1.   Monte Carlo, queuing, maintenance policy
    2.   Monte Carlo, systems simulation, computer gaming.
    3.   operational gaming, Monte Carlo, systems simulation
    4.   system simulation, operational gaming, weather forecasting
19. Which of the following as an assumption of an LP model
    1.   all of the above
    2.   Proportionality
    3.   Additively
    4.   Divisibility
20. 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.