Introduction to max-linear programming

An Introduction to Linear Programming

Lecture 15 : Introduction to Linear Programming

where x ∈ R is represents the variables, c ∈ R defines the objective function, and A ∈ Rm×n and b ∈ R define the constraints. The above form is fairly general; one can model various types of constraints in this form. For example, a constraint 〈a1, x〉 ≥ b1 can be written as 〈−a1, x〉 ≤ −b1. Or, a constraint 〈a1, x〉 = b1 can be written as 〈a1, x〉 ≤ b1 and 〈−a1, x〉 ≤ −b1. The objective function can...

Introduction to Linear and Nonlinear Programming

By reading, you can know the knowledge and things more, not only about what you get from people to people. Book will be more trusted. As this introduction to linear and nonlinear programming, it will really give you the good idea to be successful. It is not only for you to be success in certain life you can be successful in everything. The success can be started by knowing the basic knowledge a...

On the integer max-linear programming problem

For a generic class of matrices we show that integer solutions to two-sided max-linear systems and programs can be found in polynomial time. For general matrices we adapt the existing methods for finding real solutions to obtain algorithms for finding integer solutions.

A simple introduction to Karmarkar's Algorithm for Linear Programming

An extremely simple, description of Karmarkar’s algorithm with very few technical terms is given.