  In an implicit combinatorial optimization problem, the constraints are not
enumerated explicitly but rather stated implicitly through equations, other
constraints or auxiliary algorithms. An important subclass of such problems is
the implicit set cover (or, equivalently, hitting set) problem in which the
sets are not given explicitly but rather defined implicitly For example, the
well-known minimum feedback arc set problem is such a problem. In this paper,
we consider such a cover problem that arises in the study of wild populations
in biology in which the sets are defined implicitly via the Mendelian
constraints and prove approximability results for this problem.
