{"id":"W4249171336","doi":"10.22215/etd/2020-13931","title":"Combining Node and Variable Selection Heuristics for Faster MIP Solutions","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Heuristics; Selection (genetic algorithm); Heuristic; Node (physics); Variable (mathematics); Computer science; Mathematical optimization; Integer (computer science); Algorithm; Mathematics; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001682319,0.0002161121,0.0003170129,0.0001332828,0.0003155234,0.00009581431,0.0001036302,0.0002450162,0.0001995628],"category_scores_gemma":[0.001339024,0.000225788,0.00005022138,0.0002638682,0.00002082768,0.000110588,0.00003571939,0.0003202761,0.00001190917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007114528,"about_ca_system_score_gemma":0.0001512777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007066992,"about_ca_topic_score_gemma":0.00003955187,"domain_scores_codex":[0.9986977,0.0000373092,0.0003480703,0.0003545366,0.0002494123,0.0003129863],"domain_scores_gemma":[0.9985187,0.0005787298,0.0001633305,0.0001337587,0.0004944507,0.0001110351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003599806,0.0003471172,0.00004143632,0.004357367,0.000415292,0.000003095208,0.002570331,0.003125094,0.001676871,0.9329367,0.04929966,0.004867026],"study_design_scores_gemma":[0.001331798,0.0001756584,0.00001441846,0.0001760238,0.0002099226,0.000007741855,0.001503404,0.8007872,0.0009101097,0.179587,0.01472229,0.0005745406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005208903,0.00005143257,0.9825487,0.0001441511,0.000235294,0.0007979388,0.00005148141,0.0001695867,0.0159493],"genre_scores_gemma":[0.0004230709,0.00004764926,0.939854,0.00007948146,0.0001239059,0.0002027328,0.001059339,0.0001059215,0.05810387],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.797662,"threshold_uncertainty_score":0.9207366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07614927904686562,"score_gpt":0.3711716278950095,"score_spread":0.2950223488481439,"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."}}