In linear programming, redundant constraints are those that do not place any extra restrictions on the solution space, hence they have no effect on the feasible region of the problem. Stated otherwise, a redundant constraint is one that would preserve the validity of the same set of workable solutions even if it were eliminated. These constraints usually appear when a constraint is less restrictive than the current constraints or when it is a linear combination of other constraints. Repetitive constraints can be found and removed to simplify the issue, increase computational efficiency, and facilitate the search for the best solution without changing the linear programming model's general structure.

Redundant constraints are constraints in a linear programming model that do not affect the feasible region because they are either implied by other constraints or do not limit the feasible solution space further than existing constraints.

Redundant constraints in linear programming are constraints that can be removed from the problem without affecting the optimal solution. 

It is a constraints in a linear programming model that do not affect the feasible region because they are already implied by other constraints. Removing them doesn't change the optimal solution

a constraint that can be omitted from the system without changing the set of feasible solutions S.