{"id":"W4210677236","doi":"10.1007/s11750-021-00621-1","title":"A robust optimization approach for the unrelated parallel machine scheduling problem","year":2022,"lang":"en","type":"article","venue":"Top","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Job shop scheduling; Mathematical optimization; Robust optimization; Scheduling (production processes); Optimization problem; Algorithm; Schedule; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002606779,0.0001053079,0.0000953437,0.00005302686,0.0003490075,0.00004162192,0.0001738037,0.00003830695,0.0001897948],"category_scores_gemma":[0.00002082207,0.0000883657,0.00004953554,0.000302688,0.0000122548,0.00005287171,0.00003943673,0.0002110975,0.000002091359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005221111,"about_ca_system_score_gemma":0.00001482103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007376815,"about_ca_topic_score_gemma":3.37023e-7,"domain_scores_codex":[0.9993609,0.00002333179,0.0001656452,0.0001417383,0.0001310938,0.0001773264],"domain_scores_gemma":[0.9996775,0.00006114061,0.00003032801,0.0001644129,0.0000331162,0.00003343411],"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":[0.00001091631,0.00002011181,0.00001774031,0.00001689785,0.00003731906,2.95835e-7,0.0002323126,0.9980677,0.000004902927,0.0004046076,0.0001496113,0.001037543],"study_design_scores_gemma":[0.0005040264,0.00001928334,0.000003427306,0.000002350916,0.00002567673,0.000006911357,0.0002413686,0.9984831,0.00001548598,0.00003221025,0.0005447106,0.0001214562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001384455,0.0009301787,0.9958411,0.000228847,0.0002058898,0.0004399713,0.00001520487,0.0004143828,0.001785989],"genre_scores_gemma":[0.02386723,0.00004390531,0.9745748,0.00008175212,0.00007833092,0.0004385383,0.0002137246,0.00004764875,0.0006540785],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02372879,"threshold_uncertainty_score":0.3603449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.022118782462847,"score_gpt":0.2124286741142084,"score_spread":0.1903098916513614,"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."}}