What term is used to describe the feasible region in a linear programming problem?
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The feasible region in a linear programming problem, also known as the feasible set, represents all combinations of decision variable values that satisfy the constraints. It is critical for identifying the limits within which the optimal solution lies, guiding the optimization process to find the best objective function value.
The feasible region in a linear programming model is the area that includes all possible solutions satisfying the given constraints. It is typically represented graphically as a polygon in two dimensions, formed by the intersection of constraint lines. The edges of this region define the limits imposed by the constraints, while any point within the region represents a valid combination of decision variables. The optimal solution, which maximizes or minimizes the objective function, is usually found at one of the vertices of the feasible region. In summary, the feasible region encapsulates all feasible solutions that comply with the constraints of the problem.