{"id":"W2810629198","doi":"10.5267/j.ijiec.2018.2.001","title":"Trade-off in robustness, cost and performance by a multi-objective robust production optimization method","year":2018,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Robustness (evolution); Robust optimization; Mathematical optimization; Multi-objective optimization; Computer science; Reliability engineering; Production (economics); Engineering; Economics; Mathematics; Microeconomics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002528698,0.0001490407,0.000260521,0.0007843748,0.00007041736,0.000214865,0.0004243856,0.0001109253,0.00003825338],"category_scores_gemma":[0.003462284,0.0001350654,0.00006057931,0.0007287834,0.00007565058,0.0009169425,0.00006452543,0.000359805,0.00000243981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451735,"about_ca_system_score_gemma":0.0001221334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001123767,"about_ca_topic_score_gemma":0.000001983419,"domain_scores_codex":[0.9976263,0.0002248154,0.00089188,0.0002591992,0.0008423928,0.0001554224],"domain_scores_gemma":[0.9979368,0.0006664991,0.0004537507,0.00009998609,0.000745095,0.00009790256],"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":[0.0001096026,0.00008518948,0.0007572208,7.334578e-7,0.00003796313,0.000004320552,0.0004666774,0.9458471,0.001163211,0.00003241987,0.0005460407,0.05094954],"study_design_scores_gemma":[0.001283644,0.0001906088,0.001841897,0.00008933064,0.00001013811,0.0001660925,0.0002954128,0.9913653,0.004205797,0.00002175442,0.0003995829,0.000130399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1019705,0.00009160065,0.8943143,0.0007771495,0.002578828,0.0002051204,0.0000101198,0.00001647676,0.00003587962],"genre_scores_gemma":[0.5545021,0.00002245172,0.444781,0.00002500982,0.0006143809,0.00000490117,0.000004709068,0.00001441508,0.00003106202],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4525316,"threshold_uncertainty_score":0.5507807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1124628411361732,"score_gpt":0.3936420668807403,"score_spread":0.2811792257445671,"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."}}