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.

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

With fluctuating sales, a manufacturer must have fluctuating production, or fluctuating inventory, or both. Penalties are associated with either type of fluctuation. Several papers place this problem ...

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