A feasible region is the set of ordered pairs that satisfy every inequality in a system simultaneously; in context, each point represents a possible combination of quantities, with its coordinates interpreted using the specified variables and units. The boundary is included or excluded according to the inequality symbol, and the region can be used to identify feasible and infeasible choices and, when relevant, corner points for optimizing a linear objective. The focus is two-variable linear inequalities, excluding nonlinear constraints and higher-dimensional optimization.
A feasible region is the set of all points that satisfy every inequality in a system at the same time. In context, the coordinates of each point represent quantities.
Suppose a bakery makes two products:
The possible production amounts must satisfy
The inequality means the bakery makes at most total items.
The inequality means the production combination must provide at least production units.
The inequalities and mean negative quantities are not possible.
Replace each inequality with an equation to graph its boundary:
and
Because both inequalities use or , their boundary lines are solid. Points on the lines are included.
Now shade:
The overlapping shaded area is the feasible region.
Consider the point . This represents loaves and batches of muffins.
Check every inequality:
and both coordinates are nonnegative. Therefore, is feasible.
Now consider . It fails the second inequality:
Therefore, is infeasible, even though it satisfies the first inequality. A point must satisfy all the inequalities to be feasible.
The vertices, or corner points, of this feasible region are found where boundary lines meet the axes or each other:
So the feasible region has corner points
Each point represents a possible production combination. For example, means loaves and batches of muffins, while means loaves and batches of muffins.
If an inequality used a strict symbol, such as , its boundary would be dashed and points on that line would not be feasible.
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