{"id":"W4411959463","doi":"10.31449/inf.v49i23.8270","title":"Adaptive Strategy-Enhanced NSGA-II for Multi-Objective Optimization with Improved Convergence and Diversity Control","year":2025,"lang":"en","type":"article","venue":"Informatica","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Convergence (economics); Diversity (politics); Mathematical optimization; Control (management); Computer science; Mathematics; Artificial intelligence; Economics; Political science; Economic growth","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":[0.0003493065,0.0001473925,0.0002146631,0.0001667343,0.0005833029,0.0001589053,0.0004505148,0.00006214169,0.00001750707],"category_scores_gemma":[0.0002674192,0.0001222843,0.00002955903,0.0004447611,0.0001194397,0.001099062,0.0004478621,0.0001198043,0.000004040658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005932039,"about_ca_system_score_gemma":0.0002238646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002406015,"about_ca_topic_score_gemma":0.000006969882,"domain_scores_codex":[0.9989353,0.00005280039,0.0002757621,0.0002381742,0.0002273107,0.0002705972],"domain_scores_gemma":[0.99855,0.0002452111,0.0001380871,0.0002830091,0.0006827693,0.0001009049],"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":[0.001390578,0.0004946369,0.0005500606,0.0005400107,0.0009306354,0.000006324642,0.01684817,0.8005084,0.0001719168,0.09462494,0.0008486895,0.08308558],"study_design_scores_gemma":[0.00271895,0.0003357728,0.0004331729,0.00002536328,0.00002006435,0.000001401189,0.0003075794,0.9952591,0.0004950703,0.0002401218,0.00002312079,0.0001402909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003451929,0.0000174499,0.9965743,0.0001573347,0.00009011402,0.00114084,0.00002434798,0.00009139874,0.001558983],"genre_scores_gemma":[0.4081842,0.00001502398,0.5910259,0.0002194535,0.000006241884,0.00008884278,0.000005622416,0.000004010223,0.0004507568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.407839,"threshold_uncertainty_score":0.4986608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154016471860877,"score_gpt":0.2727647767679153,"score_spread":0.2512246120493065,"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."}}