The aim of this paper is to introduce a formulation of linear programming problems involving intuitionistic fuzzy variables. Here, we will focus on duality and a simplex-based algorithm for these ...

Deterministic long run average optimal control problems and, in particular, periodic optimization problems are related to certain infinite-dimensional linear programming (LP) problems, which can be ...

The dual simplex method, unlike the standard simplex method, starts with an infeasible but optimal (or better) solution for the objective function in a linear programming problem.

Tantawy, S.F. (2014) A New Concept of Duality for Linear Fractional Programming Problems. International Journal of Engineering and Innovative Technology, 3, 147-149. ... Here first we transform this ...

Dual variables can be a great asset when making decisions and improving linear programming models. For instance, you can use dual variables to identify the most binding constraints in your problem ...

ABSTRACT: The Kuhn-Tucker theorem in nondifferential form is a well-known classical optimality criterion for a convex programming problems which is true for a convex problem in the case when a ...

Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear Programming: regression, classification and other engineering applications. Integer Linear Programming: Basics, ...

The code implements the Simplex algorithm for solving linear programming (LP) problems. It takes user input for the objective function, constraints, and their types (MAX or MIN). It then iteratively ...

The first complete algorithm to solve linear programming problems, called the simplex method, was published by Dantzig in 1947 and in the same year von Neumann established the theory of duality. In ...

Linear programming (LP) solvers are crucial tools in various fields like logistics, finance, and engineering, due to their ability to optimize complex problems involving constraints and objectives.