The set of candidate solutions that satisfy all constraints is called the feasible set.

These two constraints define the feasible set of candidate solutions.

When considering a greedoid, a member of F is called a feasible set.

When considering a matroid, a feasible set is also known as an independent set.

The union of any two feasible sets is also feasible.

A poset antimatroid has as its feasible sets the lower sets of a finite partially ordered set.

Therefore, each feasible set in an antimatroid is the union of its path subsets.

The space of all candidate solutions is called the feasible region, feasible set, search space, or solution space.

Optimizing over a subset of the constraints enlarges the feasible set and will yield a solution which provides a lower bound on the objective.

The collection of all subsets of feasible sets forms a matroid.