{"id":"W52929814","doi":"10.5220/0002253403140317","title":"A NEW HYBRID GENETIC ALGORITHM FOR MAXIMUM INDEPENDENT SET PROBLEM","year":2009,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Crossover; Genetic algorithm; Heuristic; Algorithm; Computer science; Set (abstract data type); Mutation; Mathematical optimization; Population-based incremental learning; Operator (biology); Meta-optimization; Variety (cybernetics); Mathematics; Artificial intelligence; Biology","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":[0.0007724429,0.000736684,0.0008690904,0.0009809867,0.0004872771,0.0007592186,0.001350852,0.001210565,0.002509622],"category_scores_gemma":[0.001367911,0.0002850737,0.0007238511,0.001226584,0.0005675521,0.0009522371,0.0009744629,0.00102302,0.0006072909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000584549,"about_ca_system_score_gemma":0.0009092319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001626107,"about_ca_topic_score_gemma":0.001553455,"domain_scores_codex":[0.9994143,0.0001524343,0.00002067189,0.0001047985,0.0002670218,0.00004070678],"domain_scores_gemma":[0.9997368,0.0001313279,0.00002435888,0.00002838127,0.00006010941,0.00001901549],"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":[0.0001082249,0.00007992783,0.0005186473,0.0001268803,0.0001022093,0.0001500955,0.00009965077,0.6668319,0.008019337,0.05107419,0.004864009,0.2680249],"study_design_scores_gemma":[0.00005023918,0.00006284145,0.0001331495,0.00001291113,0.00002173228,0.0001070887,0.00001128101,0.977008,0.001627514,0.01286103,0.008089705,0.00001460928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006686334,0.0004236601,0.9884915,0.0001383967,0.00007921577,0.00005241563,0.00003750909,0.0003962704,0.003694741],"genre_scores_gemma":[0.1356439,0.0004970158,0.85649,0.0002103003,0.00009169072,0.0003186151,0.0002378181,0.000111659,0.006399006],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002509622,"threshold_uncertainty_score":0.008395553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02342807466795358,"score_gpt":0.2887353667167887,"score_spread":0.2653072920488351,"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."}}