ABSTRACT: The purpose of this paper is to introduce a new pivot rule of the simplex algorithm. The simplex algorithm first presented by George B. Dantzig, is a widely used method for solving a linear ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...

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

Many important practical computations, such as scheduling, combinatorial, and optimization problems, use techniques known as integer programming to find the best combination of many variables. In ...

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 ...

Resolves linear programming problems (LP) with the simplex algorithm showing all the intermediate steps. With a basic interface (Glade & GTK+) input and Latex (beamer) Output.

Abstract: This paper works on a heuristic algorithm with determinacy for the global optimization of continuous piecewise linear (CPWL) programming. CPWL is widely applied since it can be equivalently ...

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 ...

“My experiences also strongly confirmed my previous opinion that the best theory is inspired by practice and the best practice is inspired by theory.” Donald E. Knuth, “Theory and Practice,” ...