{"id":"W2230461717","doi":"10.1007/s10479-015-2091-2","title":"Exact and heuristic approaches for the cycle hub location problem","year":2016,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Bounding overwatch; Benchmark (surveying); Mathematical optimization; Metaheuristic; Theory of computation; Heuristic; Tree (set theory); Steiner tree problem; Network topology; Tree network; Set (abstract data type); Flow network; Branch and bound; Network planning and design; Routing (electronic design automation); Algorithm; 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":[0.001819282,0.00005487672,0.00007383781,0.00009757031,0.0002204599,0.00005971195,0.0001250846,0.00003789355,0.00001837031],"category_scores_gemma":[0.0007092951,0.0000334798,0.00001747788,0.0002711503,0.0001128991,0.0001490664,0.00003070938,0.00007279847,0.000006044575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001086617,"about_ca_system_score_gemma":0.00003811517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001836173,"about_ca_topic_score_gemma":0.00001610641,"domain_scores_codex":[0.9992431,0.000123589,0.000166515,0.0001124246,0.0001697144,0.0001846195],"domain_scores_gemma":[0.9985321,0.000777357,0.000008032443,0.0002087591,0.000435367,0.00003841142],"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":[0.00001053139,0.0000296632,0.0001643515,0.0001253159,0.00004169579,9.860401e-8,0.0004965828,0.8718409,0.003612077,0.01319798,0.0017832,0.1086976],"study_design_scores_gemma":[0.0001818059,0.00005473073,0.001564294,0.00004593547,0.000004197638,0.000001342935,0.0001298025,0.9850655,0.01059537,0.0009346616,0.001351774,0.00007059455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04233751,0.0009371181,0.9474937,0.006952103,0.00003391028,0.0008889505,0.00002184029,0.00006532243,0.001269492],"genre_scores_gemma":[0.9721858,0.0004228359,0.02663251,0.00001190192,0.00004887631,0.0002028915,0.000003915914,0.00001862884,0.000472641],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9298483,"threshold_uncertainty_score":0.1695622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2801187575592472,"score_gpt":0.4286605279168331,"score_spread":0.1485417703575859,"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."}}