Use of linear programming models has grown so extensively in recent years that the whole concept for organizing a computer code has undergone a radical change. It no longer is adequate merely to ...

Standard computer implementations of Dantzig's simplex method for linear programming are based upon forming the inverse of the basic matrix and updating the inverse after every step of the method.

We use the models of cognitive psychology and the early literature on linear programming models to understand how experts organize their thinking about models. We show that several different patterns ...

NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions.

Learn about the advantages of using linear programming models for data analysis in operations research, such as simplifying problems, finding optimal solutions, and communicating results.

Add a description, image, and links to the linear-programming-simplex topic page so that developers can more easily learn about it ...

Linear programming is the most fundamental optimization problem with applications in many areas including engineering, management, and economics. The simplex method is a practical and efficient ...

Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the ...

Abstract Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems ...