Valid inequalities for the feasible region of a linear program are easy to characterize. A fundamental result in linear programming is that all valid inequalities for the feasible region defined by a set of linear inequalities can be derived by simply taking non- negative linear combinations of the constraints. In other words, taking non-negative linear combinations of inequalities is a complete scheme for generating valid in- equality implied by a set of linear inequalities. We proved the following result in class: Let P = {r ER: Ax 1. That is, the set U has an odd number of vertices. Then, the inequality le s k eEE(U) is a valid inequality. Valid inequalities for the feasible region of a linear program are easy to characterize. A fundamental result in linear programming is that all valid inequalities for the feasible region defined by a set of linear inequalities can be derived by simply taking non- negative linear combinations of the constraints. In other words, taking non-negative linear combinations of inequalities is a complete scheme for generating valid in- equality implied by a set of linear inequalities. We proved the following result in class: Let P = {r ER: Ax 1. That is, the set U has an odd number of vertices. Then, the inequality le s k eEE(U) is a valid inequality