{"id":"W2065496492","doi":"10.1080/02331934.2011.590485","title":"Optimal ordering and pricing policy with supplier quantity discounts and price-dependent stochastic demand","year":2011,"lang":"en","type":"article","venue":"Optimization","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Hong Kong; City University of Hong Kong","keywords":"Mathematical optimization; Profit (economics); Nonlinear pricing; Integer programming; Dynamic programming; Economic order quantity; Product (mathematics); Mathematics; Computer science; Supply chain; Microeconomics; Economics; Business; Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002331578,0.001257379,0.002013854,0.0007946483,0.0006792561,0.002253739,0.001657809,0.002408841,0.00320167],"category_scores_gemma":[0.006239674,0.001586643,0.001018072,0.001820093,0.001365355,0.003184343,0.001222622,0.001856514,0.0003045576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002837042,"about_ca_system_score_gemma":0.002330626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01130869,"about_ca_topic_score_gemma":0.00747999,"domain_scores_codex":[0.9985527,0.0006553819,0.0000542681,0.0002093664,0.0002526978,0.0002755515],"domain_scores_gemma":[0.9973773,0.001842778,0.000302379,0.0001015277,0.0001947913,0.0001813493],"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":[0.00006777079,0.00005022023,0.0003197313,0.00005832281,0.00002584108,0.0001341149,0.00003375472,0.978411,0.0005192761,0.01631702,0.0003097577,0.003753172],"study_design_scores_gemma":[0.00001967258,0.00003050467,0.0001034633,0.000003442389,0.00001177516,0.0000175615,0.00001822996,0.9939927,0.0001752193,0.005407291,0.0002115603,0.000008467182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1556839,0.0009914858,0.8308358,0.0009031512,0.0001002024,0.0001778469,0.0002877462,0.0001682767,0.01085161],"genre_scores_gemma":[0.9021321,0.0007886253,0.0912228,0.00007094054,0.00008033274,0.0001231768,0.0001733266,0.0000699551,0.005338699],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01130869,"threshold_uncertainty_score":0.02248573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665522622321815,"score_gpt":0.2077812948908971,"score_spread":0.1911260686676789,"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."}}