1 / 9

3.4: Linear Programming

Linear Programming. Example: Suppose a Cost function is given by: C = 2x 4y and we have the constraints:x > 0, y > 0 and-x 3y < 15, 2x y < 12(Use x

irving
Download Presentation

3.4: Linear Programming

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. 3.4: Linear Programming Intro: Oftentimes we want to optimize a situation - this means to: find a maximum value (such as maximizing profits) find a minimum value (such as minimizing costs). Linear Programming: Process of optimization on a linear function Constraints: Boundaries (borders) on our function Solution Set: called Feasible Region; shaded area of possibilities given our function and our constraints.

    2. Linear Programming Example: Suppose a Cost function is given by: C = 2x + 4y and we have the constraints: x > 0, y > 0 and -x + 3y < 15, 2x + y < 12 (Use x & y intercepts to graph) Find the feasible region. Solution: We already know that x > 0 and y > 0 guarantee us an answer in the first quadrant. So let’s look at the other two.

    3. Linear Programming Since our answer has to be in the first quadrant, we know the feasible region is:

More Related