The SimplexMethod package provides an efficient implementation of the Simplex Algorithm for solving linear programming (LP) problems. It supports both maximization and minimization of objective ...

The problem of PAPR minimization is well-studied in the literature. However, most of the algorithms have high computational costs, making them impractical for real-time applications. To that end, we ...

A method is described for converting a boolean expression to a disjunctive normal equivalent (two level OR-AND circuit) which is minimal under some criterion presented in advance, as for example, the ...

MINIMIZATION-PROBLEM-WITH-LINEAR-PROGRAMMING This project explores how to solve a real-world linear programming minimization problem using Python. The objective is to find the optimal production ...

Learn how to use the dual simplex method to solve linear programming problems when the initial solution is infeasible. Find out how to formulate the dual problem, apply the algorithm, and compare ...

Introducing the Pivot Adaptive Method (PAM) - a faster variant of Gabasov's Adaptive Method (AM) for minimizing computation time. Explore the resolution of problems through successive tables and ...

The essential features of the branch-and-bound approach to constrained optimization are described, and several specific applications are reviewed. These include integer linear programming (Land-Doig ...

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