Linear and Discrete Optimization
Offered By: École Polytechnique Fédérale de Lausanne via Coursera
Course Description
Overview
This
course serves as an introduction to linear and discrete
optimization from the viewpoint of a mathematician or computer
scientist. Besides learning how linear and discrete optimization can be applied, we focus on
understanding methods that solve linear programs and discrete optimization problems in a mathematically
rigorous way.
We will answer questions like:
The course constitutes about half of the material on linear and discrete optimization that is taught for mathematics and computer science undergraduates at EPFL and will feature video lectures, quizzes, programming assignments, and a final exam.
We will answer questions like:
- Does a particular method work correctly?
- Does it terminate and, if yes, in what time?
- Can we prove that a solution is optimal?
The course constitutes about half of the material on linear and discrete optimization that is taught for mathematics and computer science undergraduates at EPFL and will feature video lectures, quizzes, programming assignments, and a final exam.
Syllabus
- Linear programming, modeling, equivalence of standard forms
- Basic solutions, primal and dual feasible basic solutions, pivoting and the simplex method
- Termination and complexity of the simplex method
- Integer programming, bipartite matching and flows
- Models of computation, bit-complexity
Taught by
Friedrich Eisenbrand
Tags
Related Courses
Linear and Integer ProgrammingUniversity of Colorado Boulder via Coursera Graph Partitioning and Expanders
Stanford University via NovoEd Discrete Inference and Learning in Artificial Vision
École Centrale Paris via Coursera Convex Optimization
Stanford University via edX Approximation Algorithms Part I
École normale supérieure via Coursera