{"id":"W1980190773","doi":"10.1016/j.disopt.2013.02.003","title":"A linear time algorithm for the Koopmans–Beckmann QAP linearization and related problems","year":2013,"lang":"en","type":"article","venue":"Discrete Optimization","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quadratic assignment problem; Mathematics; Weapon target assignment problem; Mathematical optimization; Multiplicative function; Linearization; Assignment problem; Linear bottleneck assignment problem; Generalized assignment problem; Optimization problem; Nonlinear system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009231987,0.0001675886,0.0001267388,0.00006132412,0.0001896916,0.00009606239,0.0000850104,0.0001136547,0.00009333799],"category_scores_gemma":[0.00005721086,0.0001318851,0.00003380214,0.0001519168,0.00004876491,0.0003223834,0.00002164666,0.0001033147,0.00002730818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002755455,"about_ca_system_score_gemma":0.000006689215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009845711,"about_ca_topic_score_gemma":6.235223e-7,"domain_scores_codex":[0.9992543,0.00001515519,0.0002451398,0.0001915165,0.00009551459,0.0001983414],"domain_scores_gemma":[0.9995056,0.00009287324,0.00006133907,0.0001729863,0.0001160284,0.00005118135],"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":[0.000001223258,0.000005277759,0.000003720334,0.00002457712,0.0000275743,9.028217e-8,0.0001329235,0.9869198,0.00004307713,0.0001214713,0.0002605847,0.01245964],"study_design_scores_gemma":[0.0003489055,0.00003256588,0.00005655687,0.00001908764,0.00003951677,0.000002780049,0.00002493112,0.9979522,0.0001955777,0.0005995759,0.0005488894,0.0001794083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009462376,0.0002361288,0.9973571,0.000187623,0.0001696633,0.0009347134,0.00001956093,0.0003749465,0.0006256111],"genre_scores_gemma":[0.09064643,0.001438402,0.9009346,0.00009768407,0.0002844897,0.0006936515,0.001930029,0.0002114782,0.003763232],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09642252,"threshold_uncertainty_score":0.5378119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005582494992715322,"score_gpt":0.1959777075951276,"score_spread":0.1903952126024123,"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."}}