Learn what constraints are, how to express them algebraically and graphically, and how to use them to formulate linear programming problems with examples and tips.

Learn what linear programming is, how it works, and how it can be applied to algorithm design. Discover the challenges and tips of using linear programming for optimization.

Financial portfolio management Linear programming helps in financial portfolio optimization by selecting the best mix of assets to maximize returns or minimize risk, subject to investment constraints.

Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach is used ...

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 ...

In this paper, we propose a model predictive control (MPC) algorithm using sequential convex programming (SCP) to address concave inequality constraints. Based on traditional SCP, we introduce two ...

Abstract Posterior constraint optimal selection techniques (COSTs) are developed for nonnegative linear programming problems (NNLPs), and a geometric interpretation is provided. The posterior approach ...