{"id":"W133409354","doi":"10.1007/978-3-642-37959-8_8","title":"Scheduling Using Multiple Swarm Particle Optimization with Memetic Features on Graphics Processing Units","year":2013,"lang":"en","type":"book-chapter","venue":"Natural computing series","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Particle swarm optimization; Memetic algorithm; Graphics; Scheduling (production processes); Multi-swarm optimization; Mathematical optimization; Computer graphics (images); Parallel computing; Artificial intelligence; Algorithm; Local search (optimization); Mathematics","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":[0.0002481624,0.0005611369,0.0006306388,0.000384274,0.0005734215,0.0007741879,0.001211258,0.0006303723,0.00357516],"category_scores_gemma":[0.0006347973,0.0003250067,0.0004493604,0.0009010367,0.0003001953,0.0005163793,0.0005443492,0.0007701405,0.0005238795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007507392,"about_ca_system_score_gemma":0.0005802694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003405241,"about_ca_topic_score_gemma":0.004052992,"domain_scores_codex":[0.9998606,0.00004345887,0.000006428794,0.00002286333,0.00004788803,0.00001861994],"domain_scores_gemma":[0.9998143,0.00008366165,0.00001399461,0.00002957232,0.0000420613,0.00001648785],"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":[0.0002423771,0.00007603769,0.0002749446,0.00008414856,0.00004665162,0.00009481481,0.00006229177,0.847877,0.00791475,0.01396171,0.006912429,0.1224529],"study_design_scores_gemma":[0.00001266769,0.00002448601,0.00005058945,0.000002162512,0.000004895595,0.000006900604,0.000005922054,0.9954975,0.0008565807,0.002389383,0.001145589,0.00000334717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04229065,0.001046599,0.9346832,0.0003170558,0.0005429753,0.00007890187,0.00006021051,0.001236734,0.01974367],"genre_scores_gemma":[0.5720558,0.0004232968,0.4162765,0.0001577715,0.000152545,0.0001842087,0.0001100018,0.0003297583,0.01031005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00357516,"threshold_uncertainty_score":0.01196003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388667624364467,"score_gpt":0.2713534151372267,"score_spread":0.2324866527007799,"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."}}