{"id":"W2003904481","doi":"10.1145/2598394.2598402","title":"An ant colony optimization for solving a hybrid flexible flowshop","year":2014,"lang":"en","type":"article","venue":"","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Ant colony optimization algorithms; Job shop scheduling; Computer science; Mathematical optimization; Constructive; Ant colony; Heuristic; Scheduling (production processes); Metaheuristic; Evolutionary algorithm; Artificial intelligence; Mathematics; Process (computing)","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":[0.0003954462,0.0005318862,0.0004069735,0.0004143085,0.0003608572,0.0004653268,0.0007263145,0.000831026,0.001064375],"category_scores_gemma":[0.000976562,0.0002435157,0.0004332838,0.0004487414,0.0003972631,0.0004850252,0.0004957176,0.0006189346,0.0001252884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002647008,"about_ca_system_score_gemma":0.0005293365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002178705,"about_ca_topic_score_gemma":0.002017296,"domain_scores_codex":[0.9997999,0.00006615183,0.000009202487,0.00003413828,0.00007175154,0.00001884482],"domain_scores_gemma":[0.9997621,0.0001361708,0.00002705376,0.00002012705,0.00003982722,0.00001478572],"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":[0.00002115377,0.00002811419,0.0001862783,0.00004417073,0.00002118765,0.00007336169,0.00002620146,0.966625,0.003074367,0.005971711,0.0003541126,0.02357417],"study_design_scores_gemma":[0.000006127439,0.00001827394,0.00003915214,0.000002210222,0.000003411016,0.00002020383,0.000004942504,0.9980655,0.0003342799,0.001053218,0.0004502622,0.000002303661],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03093304,0.0002260284,0.9642158,0.0001451919,0.00005085451,0.00007504816,0.000025107,0.0001546729,0.004174343],"genre_scores_gemma":[0.5205107,0.0002514809,0.4756207,0.00008806301,0.00003132864,0.0002302041,0.00006957268,0.00005371958,0.003144222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002178705,"threshold_uncertainty_score":0.004332066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009727722110353892,"score_gpt":0.2319972400880205,"score_spread":0.2222695179776666,"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."}}