Written for junior- and senior-level undergraduate students and first-year graduate students this book provides a self-contained introduction to linear programming using MATLAB. Topics …

It covers simplex, revised simplex, two-phase method, duality, dual simplex, complementary slackness, transportation, and assignment problems with good number of examples, clear …

Solve a simple linear program with linear inequalities, linear equalities, and bounds. For this example, use these linear inequality constraints:

Learn the basics of Linear Algebra in MATLAB®. Use matrix methods to analyze and solve linear systems.

Linear programming, also known as linear optimization, is minimizing or maximizing a linear objective function subject to bounds, linear equality, and linear inequality constraints.

Seventeen lab projects for teaching linear algebra designed to be solved in MATLAB

Quadratic programming (QP) is minimizing or maximizing an objective function subject to bounds, linear equality, and inequality constraints. Example problems include portfolio optimization in …

It covers simplex, revised simplex, two-phase method, duality, dual simplex, complementary slackness, transportation, and assignment problems with good number of examples, clear …

Filling the need for an introductory book on linear programming that discusses methods used to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with …

This initial relaxed LP (root node LP) and all generated LP relaxations during the branch-and-bound algorithm are solved using linear programming solution techniques.