In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables. Geometrically, each BFS corresponds to a corner of the polyhedron of feasible solutions. If there exists an optimal solution, then there exists an optimal BFS. Hence, to find an optimal solution, it is sufficient to consider the BFS-s. This fact is used by the simplex algorithm, which essentially travels from some BFS to another until an optimal one is found. (Wikipedia).
Solving One Step Equations: The Basic
This video explains how to solve basic one step equations. http://mathispower4u.wordpress.com/
From playlist Solving Basic Equations
Solving Basic Differential Equations with Integration (Differential Equations 6)
https://www.patreon.com/ProfessorLeonard How to solve very basic Differential Equations with Integration.
From playlist Differential Equations
B27 Introduction to linear models
Now that we finally now some techniques to solve simple differential equations, let's apply them to some real-world problems.
From playlist Differential Equations
Ex 1: Solve a Rational Equation (Alternative Method)
This video explains how to solve an rational equation with using a slightly different method than is normally taught. This example has an extraneous solution. Site: http://mathispower4u.com Blog: http://mathispower4.wordpress.com
From playlist Solving Rational Equations
Solve Basic Rational Equations
This video explains how to solve rational equations. http://mathispower4u.com
From playlist Solving Rational Equations
Systems of linear equations seek a common solution for the unknowns across more than one equation. It can be very simple to calculate a solution using simple algebra. Alternatively you can use elementary row operations or even lines and planes in two- and three-dimensional space. At th
From playlist Introducing linear algebra
Solution 2/2 Problem #13 Pure Roll
Solution 2/2 Problem #13 Pure Roll
From playlist Solutions to Bi-weekly Physics Problems
Linear Programming, Lecture 4. Standard form; Review on pivot process.
Sept 1, 2016. Penn State University.
From playlist Math484, Linear Programming, fall 2016
V3-04. Linear Programming. review of pivot, canonical form
Math 484: Linear Programming. review of pivot, canonical form Wen Shen, 2020, Penn State University
From playlist Math484 Linear Programming Short Videos, summer 2020
Linear Programming, Lecture 9. Artificial Variables;
Sept 20, 2016. Penn State University.
From playlist Math484, Linear Programming, fall 2016
V3-35. Linear Programming. Convexity. LP problem and edges.
Math 484: Linear Programming. Convexity. LP problem and edges. Wen Shen, 2020, Penn State University
From playlist Math484 Linear Programming Short Videos, summer 2020
Solving Equations (2 of 2: Using two methods to solve the same algebraic equation)
More resources available at www.misterwootube.com
From playlist Basic Equations
Linear Programming. Lecture 23. Adding a constraint. Integer programming-introduction
Nov. 15, 2016. Penn State University.
From playlist Math484, Linear Programming, fall 2016