{"id":"W2110620774","doi":"10.1287/opre.1120.1154","title":"An Exact Algorithm for the Capacitated Arc Routing Problem with Deadheading Demand","year":2013,"lang":"en","type":"article","venue":"Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Arc routing; Benchmark (surveying); Column generation; Mathematical optimization; Routing (electronic design automation); Computer science; Vehicle routing problem; Arc (geometry); Enhanced Data Rates for GSM Evolution; Mathematics; Artificial intelligence","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":[0.0009703804,0.001582534,0.001452502,0.001291308,0.0008299774,0.001916511,0.002353395,0.001605711,0.01290679],"category_scores_gemma":[0.003898052,0.0007684797,0.001079269,0.002348273,0.0007182005,0.00241548,0.001413039,0.001696576,0.001817148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002097143,"about_ca_system_score_gemma":0.003813878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008888902,"about_ca_topic_score_gemma":0.01126792,"domain_scores_codex":[0.9990772,0.0001644352,0.00004376156,0.0002595692,0.000261987,0.0001931057],"domain_scores_gemma":[0.9983773,0.0009601015,0.0001220193,0.0002751271,0.0001963784,0.00006907278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001339929,0.0002446973,0.0004978155,0.0002570112,0.00004205246,0.0001023188,0.00009786473,0.7137794,0.00170108,0.03400228,0.009115466,0.240026],"study_design_scores_gemma":[0.00006761406,0.00004653056,0.00009263092,0.00001361775,0.00001238022,0.00005129365,0.0000334458,0.9707741,0.0005076939,0.02617385,0.002217645,0.000009138638],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0146944,0.0003772521,0.9712478,0.000348318,0.00009813234,0.0002401858,0.0003589773,0.001794734,0.01084032],"genre_scores_gemma":[0.1382943,0.0003199333,0.8554662,0.0001730048,0.00006816189,0.000391819,0.0009878563,0.0003710571,0.003927674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01290679,"threshold_uncertainty_score":0.04317749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05729250841713738,"score_gpt":0.3586774357342097,"score_spread":0.3013849273170723,"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."}}