In an Linear programming problem, the restrictions or limitations under which the objective function is to be optimized are called

In a linear programming problem, the restrictions or limitations under which the objective function is to be optimized are called constraints. Constraints define the feasible region within which the solutions must lie. They represent the limitations in resources, capacities, or any other restrictions that might affect the decision variables. These can be equations or inequalities that bound the values of the variables, ensuring that the solution adheres to real-world limitations.

Constraints are critical in determining the optimal solution, as they define the conditions under which the objective function, which represents the goal (such as maximizing profit or minimizing cost), can be achieved. Thus, both the objective function and constraints work together to form a structured approach to the linear programming problem.