{"id":"W3136975880","doi":"10.1007/s12351-021-00629-2","title":"Modeling and solution methods for hybrid flow shop scheduling problem with job rejection","year":2021,"lang":"en","type":"article","venue":"Operational Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Tardiness; Mathematical optimization; Computer science; Heuristics; Job shop scheduling; Flow shop scheduling; Computational intelligence; Integer programming; Scheduling (production processes); Pareto principle; Schedule; Mathematics; Artificial intelligence","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":[0.001484122,0.0009308175,0.001125181,0.0006760161,0.0005888725,0.001303993,0.001834397,0.001400408,0.002347484],"category_scores_gemma":[0.002127897,0.0007269204,0.001181177,0.0007334407,0.0006093296,0.001204614,0.0009360955,0.001366964,0.0002799639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009193986,"about_ca_system_score_gemma":0.001673226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071825,"about_ca_topic_score_gemma":0.005410091,"domain_scores_codex":[0.9994932,0.0002207997,0.00002192038,0.00007688451,0.0001266508,0.00006044318],"domain_scores_gemma":[0.9989353,0.0006819247,0.0001191051,0.00003770116,0.0001813278,0.00004466679],"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":[0.00002064571,0.00002667631,0.0001191709,0.00004500703,0.00001506154,0.00001675006,0.00002063636,0.9829336,0.0004899065,0.008830504,0.0003344258,0.007147652],"study_design_scores_gemma":[0.00000165414,0.000003856473,0.0000130444,0.000001637918,0.00000176936,0.000001812439,0.000002253282,0.9986941,0.00003814727,0.001125871,0.0001146391,0.000001190194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008025221,0.0004290453,0.989141,0.0001726381,0.00007167913,0.00003660781,0.00003712031,0.00007547985,0.002011203],"genre_scores_gemma":[0.6614224,0.001211453,0.3260683,0.0001865326,0.0002269669,0.0004857589,0.0002439853,0.0001701865,0.009984336],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01071825,"threshold_uncertainty_score":0.02131176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07102026708183304,"score_gpt":0.3806921119306955,"score_spread":0.3096718448488625,"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."}}