2 ways to describe a linear programming problem:

Example Linear Programming Structuring

Linear Programming Problem

given:

  • a toy company make 2 toys: x1 and x2
  • these toys are made of 2 materials: A and B
  • to make toy x1, it needs 5 units of A and 2 units of B
  • to make toy x2, it needs 3 units of A and 3 units of B
  • there is a maximum of 30 units of A
  • there is a maximum of 20 units of B
  • each toy x1 can be sold for $10
  • each toy x2 can be sold for $7

what is the optimum product mix that maximizes the profit?

Standard/Canonical Form

Standard form is the usual and most intuitive form of describing a linear programming problem

more details Canonical Form

Equation Form
  • objective linear function:
    maximize Z = 10x1 + 7x2
  • linear constraints:
    5x1 + 3x2 ≤ 30
    2x1 + 3x2 ≤ 20
  • non-negative variable constraints:
    x1 ≥ 0
    x2 ≥ 0
Block Matrix Form

TODO

Slack/Augmented Form

Linear programming problems can be converted into an augmented form in order to apply the common form of the simplex algorithm

more details Slack Form

Equation Form
  • objective function:
    maximize Z = 10x1 + 7x2
  • augmented linear constraints:
    5x1 + 3x2 + s1 = 30
    2x1 + 3x2 + s2 = 20
  • non-negative variables:
    x1 ≥ 0
    x2 ≥ 0
  • non-negative slack variables:
    s1 ≥ 0
    s2 ≥ 0
Block Matrix Form