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 about the challenges and limitations of linear and nonlinear programming in practice, and how to overcome them with suitable models, methods, and tools.

Discover the power of realistic linear programming models with randomized constraint limits. Explore risk analysis and Monte Carlo simulation in business analytics. Perfect for graduate students.

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 ...

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 this paper, we clarify the necessary and sufficient conditions for the existence of the cell placement that satisfies the given symmetry constraints and the topology constraints imposed by a ...

In this paper, we propose an efficient decision procedure for SLA constraints, by combining a solver for difference constraints with a solver for general linear constraints. For SLA constraints, the ...