{"id":"W4376640789","doi":"10.1115/1.4062548","title":"A Dimension Selection-Based Constrained Multi-Objective Optimization Algorithm Using a Combination of Artificial Intelligence Methods","year":2023,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Benchmark (surveying); Mathematical optimization; Dimension (graph theory); Computer science; Artificial neural network; Selection (genetic algorithm); Engineering optimization; Optimization problem; Algorithm; Engineering design process; 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":[0.001410977,0.001133844,0.00146133,0.0008912949,0.0004019704,0.0006612114,0.0009771455,0.001265089,0.001660293],"category_scores_gemma":[0.001673123,0.0006053246,0.0009149789,0.0009536566,0.0005200814,0.000659647,0.00105733,0.001038444,0.0003621094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003951184,"about_ca_system_score_gemma":0.0009471686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002323019,"about_ca_topic_score_gemma":0.00211195,"domain_scores_codex":[0.9993576,0.0002533804,0.00003701902,0.0001046349,0.0001995257,0.0000477597],"domain_scores_gemma":[0.9993538,0.000360735,0.00007554099,0.00003454254,0.0001458808,0.00002948201],"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":[0.00005931558,0.00006724401,0.0005671117,0.00009420746,0.00009491855,0.00005612968,0.00003773436,0.8924746,0.00337097,0.004762104,0.001640415,0.09677529],"study_design_scores_gemma":[0.000006718162,0.0000165641,0.00004485355,0.000003384708,0.000003908614,0.00000601298,0.000001452262,0.9990851,0.0001842559,0.0004491393,0.0001962056,0.000002465903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006557456,0.0002587676,0.9916367,0.00007978561,0.00003237031,0.00004034964,0.0000163256,0.0002076302,0.001170523],"genre_scores_gemma":[0.2675619,0.0003010296,0.7278776,0.0002680032,0.00009038458,0.0005944945,0.0001741823,0.0001165921,0.003015943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002323019,"threshold_uncertainty_score":0.007462025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08441302958133033,"score_gpt":0.3691213501179116,"score_spread":0.2847083205365813,"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."}}