Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your...

5
Unit 1.6 – Linear Programming Ummmmm…yeah… I’m going to need you to go ahead and get out your notes…thanks..

Transcript of Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your...

Page 1: Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

Unit 1.6 – Linear Programming

Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

Page 2: Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

Unit 1 – Algebra: Linear Systems, Matrices, & Vertex-Edge Graphs 1.6 – Linear Programming Georgia Performance Standard:

MM3A6b – Represent and solve realistic problems using linear programming.

Page 3: Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

What’s the deal with linear programming? And when am I ever going to use this in real life? Business Piñatas Doughnuts Bikes Sunglasses Fast Cars Music

If you like any of these (or anything in the entire world) you might use linear programming.

Linear Programming lets us buy things we like and make the most of our money

Page 4: Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

Parts of Linear Programming Objective Function

What we are trying to minimize or maximize

Ex. : C = 20x + 30y Constraints

These are linear inequalities At least 3 Should intersect to form a shape called a

feasible region Shade in!

Page 5: Unit 1.6 – Linear Programming Ummmmm…yeah…I’m going to need you to go ahead and get out your notes…thanks..

Steps to Solve…

1. Figure out what you’re minimizing or maximizing

This is your objective function

2. List all your constraints3. Get the constraints into slope-intercept form

Graph these Shade in the region

4. Label the vertices These are the corners of the shapes

5. Plug in the vertices to our objective function to find the best answer