A simplified version of a multiexpose mask optimization problem is solved in order to find a compressed space in which to search for the solution to the full problem formulation. The simplification is to reduce the full problem to an unconstrained formulation. The full problem of minimizing dark region intensity while maintaining intensity above threshold at each bright point can be converted to the unconstrained problem of minimizing average dark region intensity per unit of average intensity in the bright regions. The extrema solutions to the simplified problem can be obtained for each source. This set of extrema solutions is then assessed to determine which features are predominantly printed by which source. A minimal set of extrema solutions serves as a space of reduced dimensionality within which to maximize the primary objective under constraints. The space typically has reduced dimensionality through selection of highest quality extrema solutions.