{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002403582,0.001392363,0.001724954,0.0007660862,0.0005868711,0.001952565,0.001274046,0.001152926,0.002753047],"category_scores_gemma":[0.005665103,0.00118627,0.0006840436,0.000920996,0.001408704,0.00153781,0.0009012934,0.001339582,0.000342789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002971405,"about_ca_system_score_gemma":0.003365462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007306695,"about_ca_topic_score_gemma":0.0044316,"domain_scores_codex":[0.9989699,0.0003727067,0.0000468473,0.0001663349,0.0001358994,0.0003084344],"domain_scores_gemma":[0.9952833,0.003143674,0.0007109953,0.0001759073,0.000316348,0.0003697173],"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":[0.00005833674,0.000027701,0.0001286917,0.00002433053,0.00001224221,0.00001744488,0.00001791808,0.9898784,0.0003478319,0.007290557,0.0002050672,0.001991375],"study_design_scores_gemma":[0.00002617292,0.00002764482,0.00007800939,0.000005522162,0.000006284694,0.000004759135,0.00001076686,0.9905406,0.0003032736,0.008889501,0.0001016678,0.000005849299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2043637,0.000658703,0.785286,0.000735205,0.0000633415,0.0002569256,0.000509925,0.0003944794,0.007731742],"genre_scores_gemma":[0.9367663,0.0004688592,0.06017255,0.00006291381,0.00003139075,0.0002160983,0.0002110872,0.00009544045,0.001975347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007306695,"threshold_uncertainty_score":0.02155918,"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."}}