{"id":"W2626265344","doi":"","title":"Integrated Operations Planning and Revenue Management for Rail Freight Transportation","year":2010,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; HEC Montréal","funders":"","keywords":"Profitability index; Revenue management; Profit maximization; Yield management; Revenue; Profit (economics); Bilevel optimization; Maximization; Operations research; Scheduling (production processes); Computer science; Flow network; Integer programming; Business; Operations management; Mathematical optimization; Engineering; Economics; Optimization problem; Microeconomics; Finance; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001790431,0.0006736774,0.001069979,0.0009959912,0.0004516885,0.002253818,0.000977397,0.0007627779,0.00287429],"category_scores_gemma":[0.002209232,0.0006342699,0.0006755064,0.001507964,0.0007332968,0.001736934,0.001304222,0.001160113,0.0002327172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002456142,"about_ca_system_score_gemma":0.002722374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306282,"about_ca_topic_score_gemma":0.009604067,"domain_scores_codex":[0.998693,0.0005800585,0.00004392323,0.0001472048,0.0002283825,0.000307422],"domain_scores_gemma":[0.9992738,0.0003494425,0.0001150855,0.00004508196,0.0001400503,0.00007644998],"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":[0.00003977475,0.00005266897,0.0002839369,0.00001511048,0.00001603214,0.00003080245,0.00001549627,0.9828156,0.0002292061,0.007590608,0.0002018667,0.008709048],"study_design_scores_gemma":[0.000009155885,0.00002094398,0.00009787134,0.000003268725,0.000005309136,0.000004934163,0.00001253745,0.9954069,0.0001879593,0.004012444,0.0002359387,0.000002833184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2117514,0.0005265648,0.7744603,0.0006950427,0.00005717792,0.000246622,0.0002797956,0.0002614062,0.0117216],"genre_scores_gemma":[0.9539619,0.000180263,0.04352846,0.00002530641,0.00001864171,0.00008636023,0.0001251332,0.00003499937,0.002038861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01306282,"threshold_uncertainty_score":0.02597356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270227431779715,"score_gpt":0.2613530989019162,"score_spread":0.2486508245841191,"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."}}