Lesson 7.07e

7.07e Iterations of the simplex algorithm and its graphical interpretation Quiz: OCR Further Maths, Unit 4

20 questions

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Lesson 7.07e, Iterations of the simplex algorithm and its graphical interpretation: 20 multiple choice questions for the OCR Further Maths (H245), Unit 4: Discrete Mathematics (Y544), written with Revision Ninja.

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The 20 questions

  1. In a simplex tableau, what characterises a column corresponding to a basic variable?

    • All zeros
    • All ones
    • Two ones
    • One 1 and zeros
  2. Graphically, what does a single iteration of the simplex algorithm represent?

    • Crossing boundary
    • Reflecting across axis
    • Jumping to centre
    • Moving along edge
  3. Graphically, what do the vertices of a feasible region represent in the simplex algorithm?

    • Non-basic solutions
    • Infeasible solutions
    • Unbounded solutions
    • Basic feasible solutions
  4. In a simplex problem, what value do non-basic variables take at a basic solution?

    • One
    • Objective value
    • Pivot value
    • Zero
  5. What geometric shape is formed by the set of all feasible solutions in linear programming?

    • Circle
    • Concave polygon
    • Curved surface
    • Convex polygon
  6. In the simplex algorithm for maximisation, when is the optimal solution reached?

    • No negative indicators
    • All variables basic
    • Objective row zero
    • All entries positive
  7. What defines a zero-sum game in game theory?

    • Zero total payoff
    • No pure strategies
    • Row player wins
    • All payoffs positive
  8. In a standard payoff matrix, what do positive entries usually represent?

    • Probability of winning
    • Column player gain
    • Row player loss
    • Row player gain
  9. For the row player, how is a dominated row identified in a payoff matrix?

    • All entries smaller
    • Entries are equal
    • All entries larger
    • Sum is zero
  10. For the column player, which column is dominated and can be removed?

    • Larger entry column
    • Smaller entry column
    • Zero sum column
    • Negative entry column
  11. Which rule determines the play-safe strategy for players in a matrix game?

    • Maximin or minimax
    • Maximum payoff
    • Dominant column only
    • Random choice
  12. What condition indicates that a zero-sum game has a stable solution?

    • Maximin equals minimax
    • All entries equal
    • Maximin exceeds minimax
    • Payoffs sum zero
  13. What is another term for a stable solution in a two-player zero-sum game?

    • Pivot point
    • Critical point
    • Saddle point
    • Turning point
  14. What defines a Nash Equilibrium in terms of individual player choices?

    • Zero payoff sum
    • No incentive to deviate
    • Both players win equal
    • Randomised strategy choice
  15. When must a player use a mixed strategy rather than a pure strategy?

    • Only two options
    • All payoffs positive
    • Matrix is square
    • No stable solution
  16. Graphically, how does the row player find the optimal probability in a 2xn game?

    • Midpoint of axis
    • Lowest intersection point
    • Origin
    • Highest intersection point
  17. During a simplex iteration, how is the pivot row selected?

    • Smallest negative entry
    • Absolute largest value
    • Largest positive entry
    • Smallest positive ratio
  18. For a game with no saddle point, where does the optimal probability p lie?

    • At 0 or 1
    • Always equal to 0.5
    • Greater than 1
    • Between 0 and 1
  19. In the simplex algorithm, how is the pivot column chosen for a maximisation problem?

    • Most negative indicator
    • Smallest positive ratio
    • Largest positive ratio
    • Most positive indicator
  20. What type of strategy involves a player deterministically choosing a single action every time?

    • Play-safe strategy
    • Pure strategy
    • Mixed strategy
    • Dominant strategy

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