Half 3: The algorithm underneath the hood
Up till now, this collection has lined the fundamentals of linear programming. On this article, we’re going to transfer from primary ideas into the main points underneath the hood! This text will cowl the simplex technique, which is the algorithm that’s typically used to resolve linear programming issues. Whereas we’ll remedy a easy linear programming instance by hand with the simplex technique, our focus can be on the instinct of the algorithm slightly than memorizing the algorithmic steps (we’ve computer systems for that sort of stuff!).
Right here is what we will cowl:
- Why the simplex technique is required
- Transferring from graphical options to algebraic
- Demonstrating how the simplex technique works with a easy instance
Within the first article of this collection, we went over how the attributes of linear programming enable it to solely take into account the nook factors of constraints as potential optimum options. It is a very highly effective function that narrows an infinite resolution house to a finite resolution house. Within the examples we reviewed, we solely had a couple of constraints and some variables — we even solved a few of them by hand! After taking a look at…