{"id":"W2057635030","doi":"10.1007/s10589-013-9544-9","title":"A cutting plane algorithm for the Capacitated Connected Facility Location Problem","year":2013,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Facility location problem; 1-center problem; Integer programming; Mathematical optimization; Network planning and design; Branch and cut; Set (abstract data type); Set cover problem; Integer (computer science); Mathematics; Cutting-plane method; Theory of computation; Cover (algebra); Computer science; Algorithm; Computer network; 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":[0.000201763,0.0001364411,0.0001190477,0.00006991196,0.0003833637,0.0001352482,0.0001045979,0.00006578862,0.00006592296],"category_scores_gemma":[0.00004716883,0.0001225231,0.00002688155,0.0004581875,0.00007086427,0.0001791903,0.00001614864,0.00009073527,0.0000212885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000410341,"about_ca_system_score_gemma":0.00002941904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009828112,"about_ca_topic_score_gemma":6.476814e-7,"domain_scores_codex":[0.9991594,0.00003948354,0.0003207044,0.0002037174,0.0001197129,0.0001570025],"domain_scores_gemma":[0.9985257,0.0006611241,0.00007141746,0.0001356556,0.0005376098,0.00006849453],"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":[5.954369e-7,0.00001358522,0.00002999234,0.00002561075,0.00002509795,1.203447e-8,0.000101293,0.9319238,0.00002152742,0.001596678,0.000464714,0.06579708],"study_design_scores_gemma":[0.0003329272,0.000008369966,0.000397966,0.000007411652,0.00002025283,0.000004781051,0.0001107499,0.9959162,0.00003373504,0.001664072,0.001363453,0.0001400435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001538603,0.000148538,0.9967517,0.0004370718,0.00003966841,0.001742417,0.00008319603,0.0003997451,0.0002437534],"genre_scores_gemma":[0.05044626,0.00003355201,0.9462709,0.0001560659,0.00006705113,0.002020869,0.0009115725,0.00002498626,0.00006878628],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06565703,"threshold_uncertainty_score":0.4996346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438451474703852,"score_gpt":0.2430500121766642,"score_spread":0.2286654974296257,"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."}}