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 ...

A UNSW Sydney mathematician has discovered a new method to tackle algebra's oldest challenge—solving higher polynomial equations. Polynomials are equations involving a variable raised to powers, such ...

Mitchel B. Weiss, Richard L. Menschel Professor of Management Practice at Harvard Business School, uses AI in his entrepreneurship course to generate ideas and understand public problems. His ...

Abstract: A new implementation of the Simplex method for solving linear programming problems is developed, and its application for solving MPC problems with linear objective functions is described. A ...

Solve linear optimization problems including minimization and maximization with simplex algorithm. Uses the Big M method to solve problems with larger equal constraints in Python ...

The Simplex method is an approach to solving linear programming models by hand using slack and pivot variables, also tableaus as a means to finding the optimal solution of an optimization problem. The ...

A new variant of the Adaptive Method (AM) of Gabasov is presented, to minimize the computation time. Unlike the original method and its some variants, we need not to compute the inverse of the basic ...

Abstract: This study proposes a novel technique for solving linear programming problems in a fully fuzzy environment. A modified version of the well-known dual simplex method is used for solving fuzzy ...

ABSTRACT: This study analyzes the sensitivity analysis using shadow price of plastic products. This is based on a research carried out to study optimization problem of BOPLAS, a plastic industry in ...