{"id":"W2604913432","doi":"","title":"Reaching the Elementary Lower Bound in the Vehicle Routing Problem with Time Windows","year":2013,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal; Université du Québec à Montréal","funders":"","keywords":"Column generation; Upper and lower bounds; Vehicle routing problem; Routing (electronic design automation); Relaxation (psychology); Mathematical optimization; Set (abstract data type); State space; Branch and bound; Tree (set theory); Mathematics; Path (computing); Shortest path problem; Computer science; Combinatorics","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":[0.003665589,0.001705433,0.001415801,0.0008496949,0.0007795076,0.00203556,0.001582791,0.001196296,0.004578174],"category_scores_gemma":[0.01267092,0.0004714132,0.001142204,0.001035459,0.001219705,0.003960859,0.001858461,0.002605509,0.0005349442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214624,"about_ca_system_score_gemma":0.002070954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002198844,"about_ca_topic_score_gemma":0.003051277,"domain_scores_codex":[0.9982463,0.0007388068,0.00006257871,0.0002446196,0.0003465547,0.0003611367],"domain_scores_gemma":[0.9883692,0.01000142,0.0005139573,0.0005779719,0.0002961915,0.0002412118],"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":[0.0003339525,0.0002445487,0.0007716756,0.0003729096,0.00009280357,0.0001032337,0.0002209326,0.8225111,0.004898611,0.1116958,0.001559698,0.05719467],"study_design_scores_gemma":[0.00005584215,0.0002327267,0.0003262394,0.0000508485,0.0000581875,0.00006481894,0.00009005983,0.9326108,0.004404196,0.0599211,0.00216868,0.00001653683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.107575,0.001274353,0.8737515,0.0004548079,0.00005724259,0.0002026297,0.0001421762,0.0003123398,0.01622991],"genre_scores_gemma":[0.6141213,0.001682744,0.3788238,0.0001957048,0.00007808162,0.0003297466,0.0003448426,0.0003152324,0.004108609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004578174,"threshold_uncertainty_score":0.0193857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007703593308363791,"score_gpt":0.2147546257844881,"score_spread":0.2070510324761243,"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."}}