In linear programming, a binding constraint is one that has an immediate impact on the problem's ideal solution. A binding constraint is exactly satisfied at the optimal solution, which means the solution lies on the boundary that constraint defines. Stated differently, altering a binding constraint would result in a different optimal solution. These limitations are essential for identifying the optimal point since they define the feasible region and affect the objective function's result.

A binding constraint in linear programming (LP) is a constraint that is satisfied as an equality at the optimal solution.

A binding constraint in linear programming (LP) is a constraint that holds as an equality at the optimal solution, meaning that any increase or decrease in the constraint's right-hand side would affect the feasible region and potentially the optimal solution.

A binding constraint in linear programming is a constraint that holds as an equality at the optimal solution, limiting the feasible region and impacting the decision variables. Relaxing it could change the optimal solution.

one where some optimal solution is on the line for the constraint.