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 programming is a mathematical technique that can help you optimize your objectives and constraints in a variety of problems. It can also play a crucial role in algorithm design, especially ...

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

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 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 ...

This paper focuses on constraint verification and violation resolution for Petri nets (PNs) modeling of role-based access control (RBAC) policy. Checking the satisfiability of authorization ...

1. Introduction. 1.1. The Nonnegative Linear Programming. Consider the linear programming (LP) problem ( P ) Maximize z = c T x (1) subject to. A x ≤ b (2) x ≥ 0 , (3) where c and x are n-dimensional ...