  In this article we show that the boundary of the Pareto critical set of an
unconstrained multiobjective optimization problem (MOP) consists of Pareto
critical points of subproblems considering subsets of the objective functions.
If the Pareto critical set is completely described by its boundary (e.g. if we
have more objective functions than dimensions in the parameter space), this can
be used to solve the MOP by solving a number of MOPs with fewer objective
functions. If this is not the case, the results can still give insight into the
structure of the Pareto critical set. This technique is especially useful for
efficiently solving many-objective optimization problems by breaking them down
into MOPs with a reduced number of objective functions.
