{"id":"W2766459328","doi":"10.1287/ijoc.2021.1125","title":"Convexification of Queueing Formulas by Mixed-Integer Second-Order Cone Programming: An Application to a Discrete Location Problem with Congestion","year":2022,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Mathematical optimization; Benchmark (surveying); Computer science; Queueing theory; Integer (computer science); Integer programming; Queue; Class (philosophy); Optimization problem; Mathematics","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":[0.002850223,0.001274799,0.0008964873,0.000630153,0.0004885903,0.001971662,0.0009225809,0.0008610701,0.002357795],"category_scores_gemma":[0.006269929,0.0004427263,0.001046498,0.0009262728,0.001138538,0.001329486,0.001050186,0.002891272,0.0002351484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493298,"about_ca_system_score_gemma":0.001898169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007371825,"about_ca_topic_score_gemma":0.005651475,"domain_scores_codex":[0.9990319,0.0005085472,0.0000347749,0.00008625474,0.0002320958,0.0001063986],"domain_scores_gemma":[0.9964808,0.002557133,0.0002194802,0.0001253273,0.0005106542,0.0001066453],"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":[0.00002581026,0.00006939485,0.0003193629,0.00007013101,0.00001477742,0.000112853,0.00006586967,0.8720649,0.0005456417,0.1095683,0.001911477,0.01523153],"study_design_scores_gemma":[0.000003225372,0.000009693465,0.0000241995,0.000006435201,0.000001754795,0.000008482848,0.00001250313,0.9900594,0.0001180074,0.009410487,0.0003431535,0.000002599565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009951513,0.0002802949,0.9839766,0.0003306835,0.00006442038,0.0000587641,0.00006956376,0.00006344444,0.005204631],"genre_scores_gemma":[0.5282762,0.001188445,0.4629927,0.0003008521,0.0001713094,0.0004054205,0.0002768733,0.0001994915,0.006188782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007371825,"threshold_uncertainty_score":0.0150736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202026892738359,"score_gpt":0.2368544127625243,"score_spread":0.2248341438351407,"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."}}