{"id":"W2017871062","doi":"10.1145/1389095.1389313","title":"Comparing genetic algorithm and guided local search methods by symmetric TSP instances","year":2008,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Travelling salesman problem; Genetic algorithm; Computer science; Local search (optimization); Mathematical optimization; Heuristic; Algorithm; Reciprocal; Tournament; Local optimum; Mathematics; Artificial intelligence; Combinatorics","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":[],"consensus_categories":[],"category_scores_codex":[0.001371902,0.0001858429,0.0003269321,0.0004588818,0.0003125191,0.0002111665,0.0009641534,0.00007174552,0.00008879759],"category_scores_gemma":[0.0001747415,0.0001640537,0.00004033427,0.002029464,0.0002993657,0.000343984,0.0006762876,0.0002442095,0.0000521664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007300256,"about_ca_system_score_gemma":0.0001544852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002296762,"about_ca_topic_score_gemma":0.000001486864,"domain_scores_codex":[0.9969586,0.0006605386,0.0004153377,0.0006355623,0.0008132082,0.0005168291],"domain_scores_gemma":[0.998314,0.0004538045,0.00005569589,0.0005560813,0.0002839322,0.0003365339],"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":[0.000001630045,0.00008621671,0.001242095,0.00001989837,0.0000355606,0.00005504015,0.0002477547,0.003727147,0.00006936365,0.003201499,0.006715665,0.9845982],"study_design_scores_gemma":[0.0004325044,0.00005852069,0.002653598,0.000004477882,0.000003008993,0.0001681172,0.00003002647,0.9914579,0.001869918,0.0002218935,0.002899979,0.0002000591],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009266575,0.001555843,0.9892083,0.0003048719,0.0001406705,0.0002209338,0.000001680608,0.0001598802,0.007481162],"genre_scores_gemma":[0.02398916,0.0006740153,0.9730054,0.0001417749,0.0000321363,0.0000144025,0.00000270087,0.00001448958,0.002125925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9877307,"threshold_uncertainty_score":0.6689915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08553397280728181,"score_gpt":0.3644186847723492,"score_spread":0.2788847119650674,"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."}}