Föreläsningar del 3 Flashcards

(16 cards)

1
Q

Q: What is the objective of a linear programming problem?

A

A: The maximization or minimization of a quantity, subject to constraints.

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2
Q

Q: What defines a feasible solution in LP?

A

A: A solution that satisfies all constraints of the problem.

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3
Q

Q: What is an optimal solution in LP?

A

A: A feasible solution that provides the best objective function value.

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4
Q

Q: When is a problem considered a linear programming problem?

A

A: When both the objective function and constraints are linear.

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5
Q

Q: What are the three possible outcomes of an LP problem?

A

A: Infeasibility, a unique or alternate optimal solution, or an unbounded solution.

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6
Q

Q: What is the objective function coefficient of slack and surplus variables?

A

zero

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7
Q

Q: What are extreme points in LP?

A

A: The corner points of the feasible region.

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8
Q

Q: Why are extreme points important in LP?

A

A: The optimal solution always occurs at an extreme point.

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9
Q

Q: What shapes can the feasible region take?

A

A: A single point, a line, a polygon, or an unbounded area.

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10
Q

Q: What are the main steps of the simplex method?

A

A: Formulate the problem, put it in standard form, put it in tableau form, and execute the simplex algorithm.

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11
Q

Q: What is the purpose of an artificial variable in the simplex method?

A

A: To transform constraints into equalities when there is no natural basic variable.

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12
Q

Q: When should a problem be stopped in the simplex method?

A

A: If all cj - zj values are ≤ 0, or if an artificial variable remains positive in the final tableau.

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13
Q

Q: What does it mean if all entries in an entering column are non-positive?

A

A: The LP problem has an unbounded solution.

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14
Q
  1. Q: What is a linear function?
A

A: A function where each variable appears in a separate term raised to the first power and is multiplied by a constant.

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15
Q
  1. Q: What are the three types of constraints in linear programming?
A

A: “Less than or equal to” (≤), “equal to” (=), and “greater than or equal to” (≥).

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16
Q
  1. Q: What is problem formulation in linear programming?
A

A: The process of translating a verbal statement into a mathematical statement.