{"id":"W4416118539","doi":"10.48550/arxiv.2504.05109","title":"Inverse Mixed Integer Optimization: An Interior Point Perspective","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cutting-plane method; Linear programming; Interior point method; Integer programming; Inverse; Point (geometry); Inverse problem; Norm (philosophy)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004794123,0.000529216,0.0005659445,0.0003865393,0.00009758725,0.0001193916,0.0006130159,0.000531868,0.0005054127],"category_scores_gemma":[0.0004530345,0.0006064842,0.0001998423,0.0004066997,0.00008933257,0.0002623842,0.000675356,0.001157778,0.00007234419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007241836,"about_ca_system_score_gemma":0.0001548614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009068723,"about_ca_topic_score_gemma":0.00003410719,"domain_scores_codex":[0.9978162,0.0002809883,0.0005819906,0.0007383045,0.0002009059,0.0003816066],"domain_scores_gemma":[0.9980996,0.0001040326,0.0001440565,0.001032846,0.0004430575,0.000176441],"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":[0.00001496499,0.00002939742,0.005476898,0.000150237,0.0001701743,0.0000100094,0.002197255,0.9904549,0.0001314155,0.0002209808,0.0008099976,0.0003338308],"study_design_scores_gemma":[0.0003981278,0.00003291382,0.001428384,0.000363613,0.0001108585,0.000007024191,0.001628825,0.993423,0.001206398,0.0001856174,0.0005495862,0.0006656116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1064494,0.0002204027,0.8770016,0.0004288682,0.003411868,0.0005618627,0.00006171095,0.00164939,0.01021481],"genre_scores_gemma":[0.4099354,0.0003161974,0.5853454,0.0005383753,0.0007060595,0.0002092298,0.0002747764,0.0002416322,0.002432942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3034859,"threshold_uncertainty_score":0.9996387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748786668656436,"score_gpt":0.3009208295311216,"score_spread":0.2634329628445573,"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."}}