{"id":"W2596534719","doi":"","title":"Nonsmooth Optimization through Mesh Adaptive Direct Search and Variable Neighborhood Search","year":2006,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Variable neighborhood search; Mathematical optimization; Metaheuristic; Convergence (economics); Variable (mathematics); Guided Local Search; Local search (optimization); Mathematics; Computer science; Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001696816,0.0004268617,0.0004932001,0.0006166945,0.0005694803,0.0009307277,0.001287774,0.0002984183,0.0001146058],"category_scores_gemma":[0.000245065,0.0004284745,0.00009975598,0.00226814,0.0002052666,0.001422908,0.0009552097,0.0006337141,0.00002645393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004250553,"about_ca_system_score_gemma":0.0006701141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01402006,"about_ca_topic_score_gemma":0.0002432651,"domain_scores_codex":[0.9953367,0.0006124896,0.0006105789,0.001051315,0.001177069,0.001211869],"domain_scores_gemma":[0.9971828,0.0004213884,0.0001267888,0.001312362,0.0005892461,0.0003673958],"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":[0.00004733242,0.0003219007,0.002257917,0.00003496751,0.0000535392,0.000062466,0.0002599727,0.6466078,0.0003461573,0.3392386,0.001339341,0.009430056],"study_design_scores_gemma":[0.0006195456,0.0001859778,0.002408961,0.00003310947,0.00001586304,0.00007503641,0.00004187499,0.9895931,0.002604276,0.003504055,0.0004823468,0.0004357803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003908103,0.0008378922,0.9824263,0.002157055,0.0001023426,0.001052478,0.00004246004,0.0008185778,0.01217202],"genre_scores_gemma":[0.1384316,0.0003589487,0.8579251,0.0004992933,0.0001416171,0.0002447915,0.00003951708,0.0000697747,0.002289407],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3429854,"threshold_uncertainty_score":0.9998167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488222047637413,"score_gpt":0.2463789297179581,"score_spread":0.2314967092415839,"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."}}