{"id":"W2898638454","doi":"10.5539/mas.v12n11p385","title":"Hybrid Simulated Annealing with Meta-Heuristic Methods to Solve UCT Problem","year":2018,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Simulated annealing; Tabu search; Computer science; Mathematical optimization; Heuristic; Meta heuristic; Local search (optimization); Space (punctuation); Algorithm; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01336919,0.000306722,0.0005936409,0.0007607211,0.001518519,0.0009573218,0.002157789,0.00005176153,0.0002069578],"category_scores_gemma":[0.00225713,0.0001955994,0.000124158,0.004276921,0.001328137,0.0003742847,0.0004052689,0.0002404011,0.0009491954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007883309,"about_ca_system_score_gemma":0.0004724456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005787492,"about_ca_topic_score_gemma":0.0000157349,"domain_scores_codex":[0.9941519,0.0001038334,0.0006799464,0.001635968,0.002423253,0.001005035],"domain_scores_gemma":[0.9954411,0.001102814,0.0002617488,0.0014426,0.001190942,0.0005607829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003370791,0.0002763954,0.0001954632,0.00001070016,0.0003976918,0.00002073793,0.006525414,0.3920814,0.4515193,0.03346332,0.001828704,0.1133439],"study_design_scores_gemma":[0.0003166086,0.0001661498,0.000221252,0.00001028521,0.000232609,0.00002092369,0.0001312302,0.7992118,0.04881066,0.1472663,0.003165581,0.0004465707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04524857,0.00006664322,0.9407977,0.0005188224,0.0002161594,0.0004421059,0.00001107852,0.0002116311,0.0124873],"genre_scores_gemma":[0.5853075,3.008096e-7,0.413867,0.0003834045,0.00006832036,0.00002514005,7.459849e-7,0.00001487848,0.0003326613],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.540059,"threshold_uncertainty_score":0.9998287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1935932442594671,"score_gpt":0.4494770177911564,"score_spread":0.2558837735316892,"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."}}