Learn how to use linear programming, a mathematical tool that can help you optimize your manufacturing processes and reduce costs, by finding the best combination of inputs, outputs, and constraints.

This project explores how to solve a real-world linear programming minimization problem using Python. The objective is to find the optimal production levels of two products that minimize overall ...

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 ...

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 ...

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 ...

Moreover, a new, ratio-test-free pivoting rule is proposed, significantly reducing computational cost at each iteration. Our numerical experiments show that the method is very promising, at least for ...

We conduct these optimizations via standard linear programming methods, applying general-purpose solvers to optimize over column bases of simplicial boundary matrices.