{"id":"W2616466037","doi":"","title":"A Tabu Search Heuristic for the Dimensioning of 3G Multi-Service Networks","year":2003,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Mobile Agent-Based Network Management","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Dimensioning; Tabu search; Heuristic; Computer science; A priori and a posteriori; Service (business); Mathematical optimization; Operations research; Algorithm; Artificial intelligence; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091314,0.000173139,0.0001954383,0.00007398512,0.0004266428,0.00009627709,0.0008732475,0.00007761012,0.00001451346],"category_scores_gemma":[0.00008718413,0.0001333949,0.0001028273,0.0006199268,0.00010465,0.0001134129,0.0001719216,0.0002383161,0.00001109491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009533951,"about_ca_system_score_gemma":0.00005325264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007830312,"about_ca_topic_score_gemma":0.00003680925,"domain_scores_codex":[0.9983649,0.0001897584,0.0002868267,0.000405629,0.0002892383,0.0004636261],"domain_scores_gemma":[0.9979728,0.0008647503,0.0001226209,0.0008131681,0.0001380609,0.00008862656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004537879,0.0001902106,0.001289522,0.0001668058,0.0002144684,0.00003964652,0.003214268,0.4505813,0.0002182987,0.4919962,0.007477662,0.04456629],"study_design_scores_gemma":[0.0007203341,0.00006619003,0.0008829139,0.00002973795,0.00003114975,0.000005961705,0.0001561337,0.9827958,0.0002740441,0.0006826284,0.01417304,0.0001820131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01790255,0.0009624742,0.9788896,0.0007133692,0.0004949849,0.0007452113,0.000001547398,0.00007743785,0.0002128533],"genre_scores_gemma":[0.8534145,0.0001141402,0.1435805,0.002093292,0.000103477,0.0001626202,0.000004410542,0.00002742656,0.0004996219],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8355119,"threshold_uncertainty_score":0.5439687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02220494165769431,"score_gpt":0.2350248554885643,"score_spread":0.21281991383087,"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."}}