 A similar result for square containers has been established earlier this year, using the versatile, divide-and-conquer-based Split Packing algorithm. In this paper, we present a generalized, weighted version of this approach, allowing us to construct packings of circles into asymmetric triangles. It seems crucial to the success of these results that Split Packingdoes not depend on an orthogonal subdivision structure. Beside realizing all packings below the critical density bound, our algorithm can also be used as a constant-factor approximation algorithm when looking for the smallest non-acute triangle of a given side ratio in which a given set of circles can be packed .
<meaning-changed>  A similar result for square containers has been established earlier this year, using the versatile, divide-and-conquer-based Split Packing algorithm. In this paper, we present a generalized, weighted version of this approach, allowing us to construct packings of circles into asymmetric triangles. It seems crucial to the success of these results that Split Packingdoes not depend on an orthogonal subdivision structure. Beside realizing all packings below the critical density bound, our algorithm can also be used as a constant-factor approximation algorithm when looking for the smallest non-acute triangle of a given side ratio in which a given set of circles can be packed .
 A similar result for square containers has been established earlier this year, using the versatile, divide-and-conquer-based algorithm for packing circles into various container shapes with optimal worst-case density. It employs an elegant subdivision scheme that recursively splits the circles into two groups and then packs these into subcontainers. We call this algorithm "Split Packing". It can be used as a constant-factor approximation algorithm when looking for the smallest non-acute triangle of a given side ratio in which a given set of circles can be packed .