{"id":"W2044612972","doi":"10.1016/j.procir.2014.01.072","title":"Robust Metaheuristics for Scheduling Cellular Flowshop with Family Sequence-Dependent Setup Times","year":2014,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Metaheuristic; Particle swarm optimization; Mathematical optimization; Flow shop scheduling; Job shop scheduling; Computer science; Minification; Scheduling (production processes); Robustness (evolution); Profitability index; Algorithm; Mathematics; Schedule","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":[0.0002689548,0.0002348813,0.0002461788,0.00009412767,0.0001136659,0.00009547576,0.0001941521,0.0001136659,0.00002583009],"category_scores_gemma":[0.0001828126,0.0002141641,0.00005491324,0.00018088,0.00003434638,0.000123831,0.00001803039,0.0001799022,0.00005377472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004467876,"about_ca_system_score_gemma":0.00004931783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000288182,"about_ca_topic_score_gemma":0.000002331062,"domain_scores_codex":[0.9988549,0.00001318393,0.0002436795,0.000296996,0.0002395082,0.0003517125],"domain_scores_gemma":[0.9992856,0.0001057092,0.00004899463,0.0002442793,0.0001789271,0.000136428],"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":[0.00001135183,0.00001663735,0.0001047901,0.0001800422,0.00006021218,0.000002446006,0.000172083,0.9950076,0.001658591,0.0004899747,0.0001925915,0.002103648],"study_design_scores_gemma":[0.000560972,0.00005683396,0.00001455799,0.00004499545,0.00008127878,0.000006583779,0.0001169107,0.9891715,0.008210595,0.0002356947,0.001170302,0.000329747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01671845,0.0004625667,0.9791737,0.00006173605,0.0005014869,0.0003177426,0.00002444133,0.0006828175,0.00205711],"genre_scores_gemma":[0.4348571,0.00004672263,0.5639872,0.00009724252,0.0004353621,0.0001064994,0.00007000956,0.00009848642,0.0003013793],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4181386,"threshold_uncertainty_score":0.8733359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555913918458076,"score_gpt":0.214669913453017,"score_spread":0.1891107742684363,"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."}}