What characterizes a bounded feasible region in linear programming?
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A bounded feasible region in linear programming is a finite, convex area formed by the intersection of constraint inequalities. It contains all possible solutions, with the optimal solution typically found at a vertex of this region.
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A bounded feasible region in linear programming is characterized by a finite area that contains all possible solutions that satisfy the constraints. This region is enclosed by constraint boundaries, ensuring that there are limits on the values of the decision variables. In graphical terms, a bounded feasible region does not extend infinitely in any direction, allowing for a defined optimal solution for the objective function.
A bounded feasible region in linear programming is characterized by a finite area that contains all possible solutions that satisfy the constraints. This region is enclosed by constraint boundaries, ensuring that there are limits on the values of the decision variables. In graphical terms, a bounded feasible region does not extend infinitely in any direction, allowing for a defined optimal solution for the objective function.