{"id":"W2966288920","doi":"10.1016/j.ins.2019.08.016","title":"Variable neighborhood algebraic Differential Evolution: An application to the Linear Ordering Problem with Cumulative Costs","year":2019,"lang":"en","type":"article","venue":"Information Sciences","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Università per Stranieri di Perugia; Ryerson University","keywords":"Permutation (music); Benchmark (surveying); Differential evolution; Differential (mechanical device); Suite; Variable (mathematics); Computer science; Algebraic number; Mathematics; Algorithm; Mathematical optimization; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001154544,0.0004918923,0.0009996288,0.0008143072,0.0006388355,0.001399058,0.001398787,0.001408465,0.002562691],"category_scores_gemma":[0.005104541,0.0003371924,0.0005975133,0.001448606,0.001239709,0.001299685,0.001403472,0.001399962,0.0001341466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507763,"about_ca_system_score_gemma":0.001243249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004163432,"about_ca_topic_score_gemma":0.004401939,"domain_scores_codex":[0.9997148,0.0001125008,0.00000974799,0.00003950003,0.00009474852,0.00002866714],"domain_scores_gemma":[0.9980448,0.00148658,0.0001260405,0.00006321094,0.0001792659,0.0001001038],"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":[0.00003610301,0.00005533254,0.0004210106,0.00006827901,0.00001932151,0.00009566452,0.00006685986,0.7001858,0.0007167515,0.2750815,0.0009008938,0.02235251],"study_design_scores_gemma":[0.000006012449,0.00001164345,0.00004999986,0.000003719419,0.000004245969,0.00001533743,0.000008039565,0.9744761,0.0001334854,0.02467649,0.0006104134,0.000004428063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0506906,0.0004484855,0.9368371,0.0006088468,0.0001221369,0.00006479212,0.00005207335,0.00005213671,0.0111238],"genre_scores_gemma":[0.6517032,0.0007732883,0.3342156,0.0001300175,0.0001164614,0.000157535,0.0000825025,0.00009661408,0.01272475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004163432,"threshold_uncertainty_score":0.0109396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313665831194756,"score_gpt":0.2766363749169204,"score_spread":0.2634997166049728,"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."}}