{"id":"W1967038038","doi":"10.1287/opre.51.1.160.12799","title":"Optimal Lot-Sizing/Vehicle-Dispatching Policies Under Stochastic Lead Times and Stepwise Fixed Costs","year":2003,"lang":"en","type":"article","venue":"Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Dynamic programming; Sizing; Lead time; Mathematical optimization; Computer science; Stochastic programming; Fixed cost; Production (economics); Holding cost; Operations research; Operations management; Mathematics; Economics; Microeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001086092,0.0001681066,0.0001549119,0.0005431327,0.001078314,0.001287534,0.0002295685,0.0000589911,0.0007182499],"category_scores_gemma":[0.0003537729,0.000156875,0.00003993421,0.0006395917,0.000196651,0.0009954732,0.0002790921,0.0002868245,0.0005576627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082368,"about_ca_system_score_gemma":0.00005953405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001814404,"about_ca_topic_score_gemma":0.000792991,"domain_scores_codex":[0.998252,0.00008900456,0.0002266527,0.0003569998,0.0005441108,0.0005312475],"domain_scores_gemma":[0.9992428,0.0001056445,0.00002287457,0.0003058602,0.000285569,0.0000372794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001014669,0.0004858319,0.003217794,0.0002441434,0.0001196222,0.00001948936,0.001077611,0.1145904,0.003071293,0.8386461,0.03189194,0.006534344],"study_design_scores_gemma":[0.004396716,0.0002844105,0.01157246,0.000429871,0.0001229937,0.00001487081,0.03777731,0.7938303,0.0006229588,0.003754384,0.145507,0.001686746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312021,0.000520095,0.006035287,0.004967832,0.0002754263,0.0009869282,0.000005181412,0.0001325384,0.05587465],"genre_scores_gemma":[0.9895658,0.00002399958,0.0005029097,0.0007819082,0.0004068084,0.00009647688,0.00002762271,0.00003512665,0.008559364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8348917,"threshold_uncertainty_score":0.9997492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06871421562970181,"score_gpt":0.3307891546678844,"score_spread":0.2620749390381826,"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."}}