{"id":"W2791867344","doi":"10.1007/s10898-018-0612-7","title":"Global optimization of MIQCPs with dynamic piecewise relaxations","year":2018,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Fundação para a Ciência e a Tecnologia; Ontario Research Foundation","keywords":"Mathematics; Mathematical optimization; Global optimization; Piecewise; Bilinear interpolation; Benchmark (surveying); Relaxation (psychology); Integer programming; Integer (computer science); Optimization problem; Branch and price; Nonlinear programming; Branch and bound; Nonlinear system; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001524829,0.001459537,0.0016354,0.0008956779,0.0005254867,0.001591488,0.001682379,0.001808996,0.009530558],"category_scores_gemma":[0.006012161,0.0008316677,0.0009240391,0.001242669,0.0009362343,0.001579677,0.002188558,0.002405439,0.0006555636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001089042,"about_ca_system_score_gemma":0.00123489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004712251,"about_ca_topic_score_gemma":0.003645831,"domain_scores_codex":[0.9995149,0.0002024298,0.00001726772,0.00007829869,0.00009154341,0.00009558369],"domain_scores_gemma":[0.9982302,0.001237488,0.0001259032,0.0001083621,0.0001826692,0.000115457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000600534,0.00002863323,0.0001115293,0.00009829685,0.00002199959,0.00003320607,0.00002576505,0.9672467,0.0003204191,0.02065713,0.001600374,0.00979593],"study_design_scores_gemma":[0.000007132056,0.00002605737,0.00002853021,0.00001030375,0.000005511141,0.000007411759,0.00001154247,0.9932604,0.0001030146,0.006042092,0.0004945394,0.000003382278],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02627937,0.001054557,0.9503723,0.000732681,0.0001591492,0.0001008667,0.0002809232,0.0003259782,0.02069404],"genre_scores_gemma":[0.7271041,0.0008775941,0.2555617,0.0004018099,0.0001740609,0.0004243379,0.0005751943,0.0004895317,0.01439172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009530558,"threshold_uncertainty_score":0.03188282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0186278142045024,"score_gpt":0.3480092862410984,"score_spread":0.329381472036596,"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."}}