{"id":"W2218919311","doi":"10.1109/access.2015.2508940","title":"A Multi-Objective Optimization Scheduling Method Based on the Ant Colony Algorithm in Cloud Computing","year":2015,"lang":"en","type":"article","venue":"IEEE Access","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":355,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Science Foundation of Guangdong Province; Department of Education of Guangdong Province; Guangdong University of Petrochemical Technology","keywords":"Computer science; Cloud computing; Ant colony optimization algorithms; Job shop scheduling; Mathematical optimization; Scheduling (production processes); Distributed computing; Algorithm; Routing (electronic design automation); 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":[0.0006188679,0.0008916618,0.0009924159,0.000707695,0.000601148,0.0006430583,0.001073156,0.0007175957,0.001211511],"category_scores_gemma":[0.001063676,0.0003767661,0.0009157507,0.000971683,0.0003232201,0.0007286942,0.0005121385,0.0009782014,0.000302844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005407855,"about_ca_system_score_gemma":0.001496449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007283115,"about_ca_topic_score_gemma":0.005773816,"domain_scores_codex":[0.999435,0.0002015945,0.000029405,0.00008138982,0.0002132064,0.00003924031],"domain_scores_gemma":[0.999697,0.0001144644,0.00003624755,0.00002558981,0.0001046026,0.00002215285],"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":[0.00005259502,0.00009332586,0.0003861792,0.0001402459,0.00008428829,0.0001066447,0.00006922794,0.869513,0.008431711,0.008337224,0.001933976,0.1108516],"study_design_scores_gemma":[0.000008971227,0.00001872962,0.0000562417,0.00000365706,0.000005822881,0.00001921847,0.000004318495,0.9977865,0.0005858488,0.0007464869,0.0007582756,0.000005877876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005877854,0.0003360571,0.9909931,0.0001200409,0.0001030691,0.00008413905,0.00001682619,0.0003101912,0.002158746],"genre_scores_gemma":[0.2090093,0.0005714502,0.7865123,0.0001353752,0.00008384643,0.0003853388,0.00007567197,0.0001298152,0.003096996],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007283115,"threshold_uncertainty_score":0.01448148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05571069254916829,"score_gpt":0.3316617701205856,"score_spread":0.2759510775714173,"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."}}