Algorithms to search for crystal structures that optimize some extensive property (energy, volume, etc) typically make use of random particle reorganizations in the context of one or more numerical techniques such as simulated annealing, genetic algorithms or biased random walks, applied to the coordinates of every particle in the unit cell, together with the cell angles and lengths. In this paper we describe the restriction of such searches to predefined isopointal sets, breaking the problem into countable sub-problems which exploit crystal symmetries to reduce the dimensionality of the search space. Applying this method to the search for maximally packed mixtures of hard spheres of two sizes, we demonstrate that the densest packed structures can be identified by searches within a couple of isopointal sets. For the A 2B system, the densest known packings over the entire tested range 0.2 < r_A/r_B < 2.5, including some improvements on previous optima, can all be identified by searches within a single isopointal set. In the case of the AB composition, searches of two isopointal sets generate the densest packed structures over the radius ratio range 0.2 < r _A/r_B < 5.0.
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