Constraints can be expressed as linear equations or inequalities involving decision variables and constants. For instance, if you want to maximize the profit from selling two products, X and Y ...

Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function.

Linear programming (LP) is a mathematical optimization technique used to achieve the best outcome, such as maximum profit or minimum cost, ...

The goal of linear programming is to find the optimal solution that satisfies all the constraints while optimizing the objective function. Formulate a minimization problem; Formulate a maximization ...

Discover a groundbreaking active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving linear programming problems. Explore strategies to bound initial problems and add multiple ...

In the linear programming approach to approximate dynamic programming, one tries to solve a certain linear program - the ALP -, which has a relatively small number K of variables but an intractable ...

Abstract: In this paper, we discuss linear programs in which the data that specify the constraints are subject to random uncertainty. A usual approach in this setting is to enforce the constraints up ...

We describe a new active-set, cutting-plane Constraint Optimal Selection Technique (COST) for solving general linear programming problems. We describe strategies to bound the initial problem and ...