{"id":"W1745273410","doi":"10.3233/ica-2010-0344","title":"A multi-criteria optimization framework for industrial shop scheduling using fuzzy set theory","year":2010,"lang":"en","type":"article","venue":"Integrated Computer-Aided Engineering","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Computer science; Mathematical optimization; Fuzzy logic; Fuzzy set; Scheduling (production processes); Industrial engineering; Mathematics; Artificial intelligence; Engineering","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":[0.002755933,0.001696906,0.002097172,0.001356316,0.0009066893,0.001979917,0.002297267,0.001474697,0.00294274],"category_scores_gemma":[0.002325215,0.0008018035,0.002147666,0.001812721,0.0009324499,0.00131249,0.001234353,0.001526376,0.0005231221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002054045,"about_ca_system_score_gemma":0.002267963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01167447,"about_ca_topic_score_gemma":0.008008398,"domain_scores_codex":[0.9986162,0.0005547621,0.0000785397,0.0001752487,0.0004618256,0.0001133821],"domain_scores_gemma":[0.9992465,0.0004364054,0.00007912661,0.00002838259,0.0001662839,0.00004333957],"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":[0.00001749226,0.00003993535,0.00007910633,0.00008832172,0.0000502665,0.00007083218,0.00005214482,0.9505425,0.0006984555,0.03376594,0.0005885102,0.01400655],"study_design_scores_gemma":[0.000008982195,0.00002432575,0.00003356547,0.00001451424,0.00001057395,0.00001040143,0.000009304638,0.989167,0.0001080044,0.00990539,0.0007000503,0.000007835956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001706708,0.0002880417,0.9959823,0.00007928441,0.00003002901,0.00004819784,0.00002778872,0.00004756504,0.001790144],"genre_scores_gemma":[0.3153834,0.001124979,0.6780102,0.0001145531,0.0001379269,0.0007200807,0.0001885566,0.00008197196,0.004238397],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01167447,"threshold_uncertainty_score":0.02321303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03596246882074433,"score_gpt":0.2718421789509948,"score_spread":0.2358797101302504,"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."}}