{"id":"W1973799058","doi":"10.1007/s10957-007-9263-4","title":"New Branch-and-Cut Algorithm for Bilevel Linear Programming","year":2007,"lang":"en","type":"article","venue":"Journal of Optimization Theory and Applications","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Transpose; Branch and bound; Mathematics; Branch and cut; Bilevel optimization; Linear programming; Algorithm; Integer programming; Theory of computation; Mathematical optimization; Branching (polymer chemistry); Set (abstract data type); Optimization problem; Computer science","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":[0.001734072,0.001740529,0.003278204,0.001758877,0.001101937,0.002246084,0.002466322,0.002894373,0.009772832],"category_scores_gemma":[0.004286913,0.001551196,0.001105667,0.00260859,0.0009500926,0.002605068,0.002726729,0.004134641,0.001719838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00097131,"about_ca_system_score_gemma":0.002312121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003200371,"about_ca_topic_score_gemma":0.005152469,"domain_scores_codex":[0.9990421,0.0002761515,0.00005800319,0.000136871,0.0003931199,0.00009372429],"domain_scores_gemma":[0.9985051,0.0007542033,0.00007002623,0.000128809,0.0004310315,0.0001108511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004603315,0.000458022,0.0005541525,0.000350309,0.000176579,0.0001266697,0.00011848,0.3705539,0.003669339,0.05867083,0.01509829,0.5497631],"study_design_scores_gemma":[0.00007211687,0.00003845866,0.00004611208,0.00001801023,0.00001614508,0.00002827166,0.000009559443,0.9813033,0.0005293069,0.01563827,0.002290407,0.00001007878],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002532291,0.0002403391,0.9945636,0.000136972,0.0001021237,0.00005237653,0.00005504635,0.0004757665,0.001841514],"genre_scores_gemma":[0.03781828,0.0002228228,0.9577699,0.0001278525,0.00009236793,0.0002506086,0.0002843589,0.0003318314,0.003101859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009772832,"threshold_uncertainty_score":0.03269339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117445259928318,"score_gpt":0.2768035725164913,"score_spread":0.2656291199172081,"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."}}