{"id":"W2160597848","doi":"10.1287/opre.1120.1060","title":"Technical Note—On Optimal Policies for Inventory Systems with Batch Ordering","year":2012,"lang":"en","type":"article","venue":"Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematical optimization; Series (stratigraphy); Integer (computer science); Markov chain; Computer science; Markov decision process; Order (exchange); Time horizon; Batch processing; Multiple; Markov process; Mathematics; Economics; Statistics; Finance","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":[0.006286359,0.001746848,0.002035417,0.00121927,0.001365985,0.002965212,0.002345065,0.002067537,0.01056287],"category_scores_gemma":[0.02047374,0.001078264,0.0016941,0.002532889,0.002946863,0.007384299,0.002862527,0.003477559,0.0009200217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00248086,"about_ca_system_score_gemma":0.003378269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00428673,"about_ca_topic_score_gemma":0.002113336,"domain_scores_codex":[0.9970677,0.001587706,0.0001299424,0.000351718,0.0005460763,0.0003168565],"domain_scores_gemma":[0.9861597,0.01145028,0.0007842475,0.0004745673,0.000783309,0.0003479156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002295408,0.0001876642,0.0007645157,0.0005092575,0.00009863778,0.00020381,0.000191814,0.5148149,0.002165715,0.4446726,0.01174665,0.02441499],"study_design_scores_gemma":[0.00005845193,0.0001537308,0.0003105095,0.0001415332,0.00004913409,0.00009516846,0.00007092339,0.6858194,0.0009324652,0.3036827,0.00864483,0.00004117842],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01718911,0.005422217,0.9354602,0.003908418,0.0006294973,0.0002244523,0.0004428383,0.0002306798,0.03649271],"genre_scores_gemma":[0.683235,0.017786,0.2733634,0.002298029,0.003657567,0.0005501563,0.000764492,0.0005805126,0.01776481],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01056287,"threshold_uncertainty_score":0.03533632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1046541837346989,"score_gpt":0.358237815793805,"score_spread":0.2535836320591061,"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."}}