{"id":"W1994932713","doi":"10.1007/s10479-008-0481-4","title":"A branch-and-cut algorithm based on semidefinite programming for the minimum k-partition problem","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Direktion für Entwicklung und Zusammenarbeit","keywords":"Mathematics; Semidefinite programming; Rounding; Partition (number theory); Combinatorics; Hyperplane; Disjoint sets; Algorithm; Graph partition; Maximum cut; Partition problem; Branch and cut; Integer programming; Graph; Computer science; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001451454,0.001440223,0.002670845,0.001183141,0.00124598,0.002108499,0.002393821,0.002014278,0.007648276],"category_scores_gemma":[0.004717263,0.001147858,0.001251047,0.001880147,0.001094191,0.00302576,0.002408297,0.003921451,0.001353094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115933,"about_ca_system_score_gemma":0.002449812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002203802,"about_ca_topic_score_gemma":0.003490811,"domain_scores_codex":[0.9991224,0.0003297583,0.00004108178,0.0001868481,0.0002161812,0.0001036974],"domain_scores_gemma":[0.9977058,0.00153306,0.0001357663,0.0001974412,0.000247069,0.0001809017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006344416,0.0007815122,0.0005863391,0.0003468363,0.0001192927,0.0001394071,0.0002237786,0.5308565,0.005237564,0.1206509,0.02049531,0.3199282],"study_design_scores_gemma":[0.0000985533,0.00008005093,0.00007769006,0.00001848372,0.00001754313,0.00004659455,0.00002520025,0.947179,0.0006394323,0.05070549,0.001097598,0.00001443355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01368831,0.0001529671,0.9804901,0.0003902175,0.00007794435,0.0001273887,0.0001247063,0.0004258831,0.004522387],"genre_scores_gemma":[0.1141178,0.0002076734,0.8807108,0.0002082003,0.00008845768,0.0003881557,0.0005649176,0.0003077759,0.003406073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007648276,"threshold_uncertainty_score":0.02558607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2635310348025377,"score_gpt":0.4164277997338451,"score_spread":0.1528967649313074,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}