Benchmark Sets and Experimental Results for "High-Quality Multi-Constraint Hypergraph Partitioning via Greedy Rebalancing"

set_h.zip: benchmark set of 50 small to medium hypergraphs with 2-dimensional node weights (unit weights, degree) set_v.zip: benchmark set of 27 small to medium hypergraphs from VLSI design with 3-dimensional node weights (unit weights, degree, area of component) set_v_prime.zip: identical to Set V, but with 3 additional weight dimensions containing uniform random weights (6 dimensions in total) set_r.zip: benchmark set of 33 large regular graphs (i.e., graphs with low degree variance, such as mesh graphs) with 2-dimensional node weights (unit weights, degree) set_i.zip: benchmark set of 34 large irregular graphs (i.e., graphs with high degree variance, such as social networks) with 2-dimensional node weights (unit weights, degree) stats_hg.csv: general statistics for Set H stats_vlsi.csv: general statistics for Set V stats_regular.csv: general statistics for Set R stats_irregular.csv: general statistics for Set I results_ablation.zip: experimental results for our ablation study results_refinement.zip: experimental results for our evaluation of refinement algorithms results_fallback.zip: experimental results for our evaluation of fallback rating functions results_comparison.zip: experimental results for our comparison to the state of the art