{"id":"W3111000592","doi":"10.1007/978-3-030-58930-1_12","title":"Hybridization of the Differential Evolution Algorithm for Continuous Multi-objective Optimization","year":2020,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Mathematical optimization; Differential evolution; Metaheuristic; Computer science; Convergence (economics); Algorithm; Evolutionary algorithm; Multi-objective optimization; Meta-optimization; Mathematics","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":[0.0008907944,0.000614882,0.000976262,0.0006850173,0.0003028876,0.001024118,0.001269449,0.001269458,0.00611986],"category_scores_gemma":[0.001997545,0.0003435038,0.0007723137,0.0012199,0.0004967883,0.001010353,0.001213618,0.001451967,0.001269591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004948062,"about_ca_system_score_gemma":0.0004292983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009038071,"about_ca_topic_score_gemma":0.0009143074,"domain_scores_codex":[0.9995311,0.0001453979,0.00002072199,0.00006061652,0.0002125389,0.00002955137],"domain_scores_gemma":[0.9994904,0.0002890786,0.00001842148,0.00006067987,0.0001143248,0.0000270264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000121076,0.0002098506,0.0005271082,0.0003135298,0.0001460522,0.0001504282,0.00016753,0.4295804,0.01426416,0.09842187,0.004555309,0.4515427],"study_design_scores_gemma":[0.00001442901,0.0000702927,0.0001468024,0.00001983727,0.00001395105,0.00006684643,0.0000119271,0.9781988,0.001607138,0.01139682,0.008442674,0.0000105683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008942549,0.0009934776,0.9675184,0.0001847059,0.0003009696,0.00004864787,0.00002819134,0.0003384705,0.02164457],"genre_scores_gemma":[0.21535,0.001009938,0.7619762,0.0002645864,0.0001592393,0.0002308173,0.0001260397,0.0002290999,0.02065402],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00611986,"threshold_uncertainty_score":0.02047294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05448713278363557,"score_gpt":0.3238692042405703,"score_spread":0.2693820714569347,"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."}}