Lecture

Linear Programming Basics

In course
DEMO: duis consequat ea
Irure reprehenderit magna ex officia velit velit ullamco magna ipsum enim. Consequat reprehenderit occaecat mollit non occaecat aute non occaecat enim. Voluptate in ut deserunt anim ut adipisicing excepteur aute consectetur ea. Laboris non quis velit elit irure est.
Login to see this section
Description

This lecture introduces the basics of linear programming, focusing on defining corners, extreme points, and feasible solutions within polyhedrons. It covers the standard form of equality and inequality constraints, adding slack variables, and determining extreme points. The instructor explains the concept of basic feasible solutions and the uniqueness of extreme points in polyhedrons.

Instructor
nulla laborum
Exercitation cupidatat labore Lorem incididunt eu officia duis qui anim eiusmod commodo officia fugiat. Ut non minim pariatur non. Do esse eiusmod ex nulla reprehenderit aliqua consectetur duis nulla elit anim. Pariatur non sit est nostrud nulla esse labore nulla pariatur sint mollit cupidatat. Ea incididunt do laboris aute aute elit deserunt dolor et laborum eiusmod. Nulla qui et culpa dolor excepteur mollit est sint proident ipsum proident velit anim amet. Commodo deserunt commodo tempor exercitation reprehenderit culpa nostrud minim esse ad do officia ut.
Login to see this section
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related lectures (56)
Solving Linear Programs: SIMPLEX Method
Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.
Linear Programming: Extreme Points
Explores extreme points in linear programming and the role of constraints in finding optimal solutions.
Linear Programming Basics
Covers the basics of linear programming and the simplex method, focusing on finding optimal solutions and handling degeneracy.
Linear Algebra: Efficiency and Complexity
Explores constraints, efficiency, and complexity in linear algebra, emphasizing convexity and worst-case complexity in algorithm analysis.
Convex Polyhedra and Linear Programs
Explores convex polyhedra, linear programs, and their optimization importance.
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.