{"id":"W2051358678","doi":"10.1287/opre.1060.0283","title":"A Branch-and-Cut Algorithm for the Dial-a-Ride Problem","year":2006,"lang":"en","type":"article","venue":"Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":672,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Branch and cut; Travelling salesman problem; Vehicle routing problem; Computer science; Integer programming; Mathematical optimization; Set (abstract data type); Routing (electronic design automation); Branch and price; 2-opt; Traveling purchaser problem; Algorithm; Mathematics; Computer network","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00131969,0.00007237522,0.00007705641,0.0001001703,0.0005786,0.0002474624,0.0001390992,0.00005021537,0.00004148289],"category_scores_gemma":[0.0001269086,0.00005594532,0.00002514383,0.0003682992,0.00007633612,0.000115517,0.00003906368,0.0002053596,0.00002153515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004661217,"about_ca_system_score_gemma":0.00004283148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002052139,"about_ca_topic_score_gemma":0.0002083557,"domain_scores_codex":[0.9990987,0.0001099655,0.0001606114,0.0001387428,0.0002130572,0.0002789523],"domain_scores_gemma":[0.9990296,0.0005066628,0.000003732073,0.0002031978,0.0002192307,0.00003757239],"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":[0.000001512193,0.00001529487,0.00004325329,0.00001984279,0.00001561773,5.008947e-7,0.0001732721,0.8714188,0.002853279,0.003893735,0.003926619,0.1176382],"study_design_scores_gemma":[0.0002114469,0.00001539019,0.0002627453,0.000007405521,0.000004345769,0.000004332659,0.0000339765,0.9854132,0.002867009,0.0003565242,0.01075242,0.00007120999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004125947,0.0004089767,0.9898782,0.001148059,0.00007325748,0.0008260225,0.00002457889,0.0001299088,0.003385094],"genre_scores_gemma":[0.214568,0.0001895901,0.7757881,0.00003309386,0.0005866443,0.001116139,0.0000431839,0.00007318611,0.007602034],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.21409,"threshold_uncertainty_score":0.4450182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04499379721732293,"score_gpt":0.3588639218862965,"score_spread":0.3138701246689736,"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."}}