{"id":"W2106889879","doi":"10.5555/1486693.1486717","title":"Solving large scale optimization problems by opposition-based differential evolution (ODE)","year":2008,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Ontario Tech University","funders":"","keywords":"Ode; Differential evolution; Initialization; Computer science; Mathematical optimization; Benchmark (surveying); Test suite; Suite; Applied mathematics; Algorithm; Mathematics; Test case; Machine learning","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":[0.001085261,0.0004404619,0.0006249683,0.0004238856,0.000240563,0.0006384283,0.0005893742,0.0007369824,0.001067201],"category_scores_gemma":[0.002144718,0.0001866247,0.0005448626,0.0004588294,0.000464304,0.0004342537,0.0006969572,0.0005803862,0.0001738844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004464483,"about_ca_system_score_gemma":0.0003784068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00122873,"about_ca_topic_score_gemma":0.0007493943,"domain_scores_codex":[0.9996234,0.0001614036,0.00002132258,0.00003732196,0.0001299974,0.00002645993],"domain_scores_gemma":[0.998984,0.0007571189,0.00007456308,0.00004762493,0.0001124732,0.00002420279],"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":[0.00004895409,0.00004974403,0.0007069935,0.00009883756,0.00005647272,0.00006898092,0.00003444916,0.9581851,0.003535043,0.006073828,0.000310459,0.0308311],"study_design_scores_gemma":[0.000008661109,0.00003373141,0.00008105137,0.000004462304,0.000004572976,0.00001725282,0.000004049536,0.9980069,0.0006191404,0.0007708748,0.000446564,0.000002801769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07036367,0.0004163704,0.919126,0.0002092404,0.00007514776,0.00008633647,0.00003797162,0.0001462452,0.009539117],"genre_scores_gemma":[0.7958851,0.0003194422,0.2002834,0.0001242262,0.00002829044,0.0002094895,0.00009243114,0.00004445904,0.003013228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00122873,"threshold_uncertainty_score":0.00573951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01513323171256287,"score_gpt":0.2394451487775571,"score_spread":0.2243119170649942,"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."}}