A binding constraint is a limitation in a linear programming problem that restricts the feasible solution space and directly affects the optimal solution; it occurs when a constraint is satisfied as an equality at the optimal solution. Shadow prices are associated with binding constraints and represent the value of an additional unit of a resource; specifically, the shadow price indicates how much the objective function (such as profit or cost) would improve if the constraint were relaxed by one unit. In essence, shadow prices provide insight into the worth of resources constrained by binding limits, guiding decision-makers on where to allocate resources for maximum benefit.

A binding constraint in Linear Programming (LP) is a constraint that is active or fully utilized at the optimal solution. This means that the solution lies exactly on the boundary defined by the constraint, and any increase or decrease in the right-hand side of this constraint will directly affect the optimal solution.