Figure 1 A typical regulator output programming network where the Vsense feedback node and values for R1 varies from type to type. Quantitatively, the Vsense feedback node voltage varies from type to ...

Introduction: This study focuses on broadening the applicability of the metaheuristic L1-norm fitted and penalized (L1L1) optimization method in finding a current pattern for multichannel transcranial ...

Optimization Theory is a branch of mathematics devoted to solving optimization problems…where we want to minimize or maximize the function value. These types of problems are found numerously 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.

The purpose of this research paper is to introduce Easy Simplex Algorithm which is developed by author. The simplex algorithm first presented by G. B. Dantzing, is generally used for solving a Linear ...

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: A global convergent algorithm is proposed to solve bilevel linear fractional-linear programming, which is a special class of bilevel programming. In our algorithm, replacing the lower level ...