{"id":"W2053093378","doi":"10.1016/s0898-1221(02)00202-x","title":"Min-max formulation of the balance number in multiobjective global optimization","year":2002,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Mathematics; Pareto principle; Mathematical optimization; Multi-objective optimization; Norm (philosophy); Set (abstract data type); Representation (politics); Pareto interpolation; Pareto optimal; Applied mathematics; Computer science; Statistics; Extreme value theory","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":[0.003114911,0.001918044,0.00147664,0.00107159,0.0008337108,0.002161951,0.00163742,0.001588941,0.007620262],"category_scores_gemma":[0.005707419,0.0008653546,0.0006765437,0.001155862,0.001369698,0.003261663,0.001408066,0.001901079,0.0007930967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001347032,"about_ca_system_score_gemma":0.001032747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001381572,"about_ca_topic_score_gemma":0.00190881,"domain_scores_codex":[0.999333,0.0003349586,0.00002245909,0.00009085969,0.0001685526,0.00005012038],"domain_scores_gemma":[0.9990517,0.0006872588,0.00008049323,0.00003611454,0.0001034865,0.00004085813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001676913,0.00005963105,0.0002846391,0.0003719538,0.0000438095,0.00006953901,0.00009946072,0.7380644,0.002077938,0.1996735,0.004371491,0.05471596],"study_design_scores_gemma":[0.00002065798,0.00006458104,0.0001348873,0.0000422521,0.00001501501,0.00003264357,0.00002732755,0.8849378,0.0008545211,0.110485,0.003372626,0.00001286655],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007545208,0.0006410623,0.9752365,0.0004120946,0.0001500595,0.00008366001,0.0001159843,0.00008988909,0.01572541],"genre_scores_gemma":[0.4239473,0.001322688,0.5489055,0.0003703976,0.0003547849,0.0008217488,0.0003267798,0.0005464831,0.02340427],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007620262,"threshold_uncertainty_score":0.02549237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02741721576649902,"score_gpt":0.3147388651313603,"score_spread":0.2873216493648613,"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."}}