Decision Science | Chapter 1 | Part 1 | MBA MCQs | DS

Decision Science MCQs

  

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1. Linear programming is a
   
   1.   Technique for economic allocation of limited resources
   2.   All of the above
   3.   Technique for economic allocation of limited resources
   4.   Constrained optimization technique
2. The qualitative approach to decision analysis relies on
   1.   Experience
   2.   Intuition
   3.   All of the above
   4.   Judgement
3. The distinguishing feature of an LP model is
   1.   All of the above
   2.   Value of decision variables is non-negative
   3.   Relationship among all variables is linear
   4.   It has single objective function & constraints
4. A model is
   1.   An idealization
   2.   All of the above
   3.   An approximation
   4.   An essence of reality
5. The use of decision models
   1.   Reduces the scope of judgement & intuition known with certainty in decision-making
   2.   Is possible when the variables value is known
   3.   Require the use of computer software
   4.   None of the above
6. The quantitative approach to decision analysis is a
   1.   Scientific approach
   2.   All of the above
   3.   Rational approach
   4.   Logical approach
7. Constraints in an LP model represents
   1.   Requirements
   2.   Balancing limitations & requirements
   3.   All of the above
   4.   Limitations
8. The mathematical model of an LP problem is important because
   1.   It enables the use of algebraic technique
   2.   It captures the relevant relationship among decision factors
   3.   Decision-makers prefer to work with formal models
   4.   It helps in converting the verbal description & numerical data into mathematical expression
9. For analyzing a problem, decision-makers should study
   1.   Its qualitative aspects
   2.   Neither a nor b
   3.   Its quantitative aspects
   4.   Both a & b
10. Managerial decisions are based on
    1.   The use of qualitative factors
    2.   All of the above
    3.   An evaluation of quantitative data
    4.   Results generated by formal models
11. Non-negativity condition is an important component of LP model because
    1.   Value of variables make sense & correspond to real-world problems
    2.   Variables are interrelated in terms of limited resources
    3.   None of the above
    4.   Variables value should remain under the control of the decision-maker
       b.
12. Its quantitative aspects
    1.   None of the above
    2.   Uncontrollable
    3.   Controllable
    4.   Parameters
13. Before formulating a formal LP model, it is better to
    1.   All of the above
    2.   Express each constrain in words
    3.   Express the objective function in words
    4.   Verbally identify decision variables
14. A physical model is example of
    
    1.   An iconic model
    2.   A verbal model
    3.   A mathematical model
    4.   An analogue model
15. An optimization model
    1.   Helps in evaluating various alternatives
    2.   Provides decision within its limited context
    3.   Provides the best decision
    4.   All of the above
16. Decision Science approach is
    1.   All of the above
    2.   Intuitive
    3.   Scientific
    4.   Multi-disciplinary
17. Which of the following is not a characteristic of the LP model
    1.   Limited amount of resources
    2.   Non-negativity condition on the value of decision variables
    3.   An objective function of maximization type
    4.   Alternative courses of action
18. A constraint in an LP model restricts
    1.   Value of a decision variable
    2.   All of the above
    3.   Use of the available resources
    4.   Value of objective function
19. Every mathematical model
    
    1.   Requires computer aid for its solution
    2.   Must be deterministic
    3.   All of the above
    4.   Represents data in numerical form
20. Maximization of objective function in an LP model means
    
    1.   Value occurs at allowable set of decisions
    2.   Both a & b
    3.   Highest value is chosen among allowable decisions
    4.   Neither of above