{"id":"W223119275","doi":"10.1023/a:1026102724889","title":"A Tabu Search with Slope Scaling for the Multicommodity Capacitated Location Problem with Balancing Requirements","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Tabu search; Initialization; Mathematical optimization; Heuristic; Integer programming; Theory of computation; Scaling; Mathematics; Integer (computer science); Computer science; Scale (ratio); Algorithm","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":[0.001974664,0.00106046,0.001716798,0.001766604,0.0008564771,0.001286345,0.002148462,0.0022897,0.01090311],"category_scores_gemma":[0.006198181,0.0009658962,0.001033271,0.002922848,0.0008112732,0.001814754,0.00135317,0.001542431,0.001400377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007342845,"about_ca_system_score_gemma":0.001691586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006081879,"about_ca_topic_score_gemma":0.00519607,"domain_scores_codex":[0.999202,0.0004734156,0.00002728562,0.00008009555,0.0001256743,0.00009161298],"domain_scores_gemma":[0.9980478,0.001359637,0.000099089,0.0001465216,0.0002639993,0.00008294496],"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":[0.0003245753,0.0002560845,0.0008202047,0.0001445128,0.00005522263,0.00005184545,0.0001190109,0.8285403,0.0009834782,0.006954312,0.006870916,0.1548795],"study_design_scores_gemma":[0.00007498864,0.0000817194,0.0001081601,0.00001851031,0.00001333802,0.00001174122,0.00002879977,0.9955011,0.0001352949,0.003403436,0.0006148763,0.000007960608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1147306,0.002321695,0.8559616,0.001000592,0.0003249552,0.0005427205,0.0005888502,0.002979415,0.0215496],"genre_scores_gemma":[0.3227196,0.0005120856,0.670531,0.0003467359,0.0001116492,0.0005618635,0.0005714545,0.0004444736,0.004201186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01090311,"threshold_uncertainty_score":0.03647459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2083074404042083,"score_gpt":0.4026867677618781,"score_spread":0.1943793273576698,"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."}}