Lecture
The Simplex Algorithm: Efficiency and Degeneracy
Description
This lecture covers the Simplex Algorithm, focusing on efficiency and degeneracy. It explains how to compute reduced costs, determine optimality, handle unbounded costs, and update the basis. The lecture also discusses degenerate cases, cycling, and termination conditions. The instructor emphasizes the importance of selecting pivot elements carefully to avoid cycling and achieve finite convergence.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on MediaspaceInstructor
sit proident
Mollit deserunt reprehenderit consequat consequat elit ipsum sit ut. Et deserunt aliquip dolor nostrud et ullamco. Laboris quis magna velit et duis minim.
Official source
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.
Ontological neighbourhood
Related lectures (35)
The Simplex Algorithm
Covers the Simplex Algorithm, explaining optimality, unbounded costs, and degenerate problems.
Matrix Similarity and Diagonalization
Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.
Solving Linear Programs: SIMPLEX Method
Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.
Characteristic Polynomials and Similar Matrices
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Matrix Representations of Linear Applications
Covers matrix representations of linear applications in R³ and the invariance of rank.