{"id":"W1966325083","doi":"10.1016/j.ijpe.2003.07.002","title":"Multi-product capacity-constrained lot sizing with economic objectives","year":2003,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Sizing; Queueing theory; Computer science; Economic order quantity; Mathematical optimization; Queue; Production (economics); Product (mathematics); Holding cost; Throughput; Operations research; Microeconomics; Economics; Mathematics; Business; Computer network","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":[],"consensus_categories":[],"category_scores_codex":[0.0003422892,0.0001345963,0.0001718787,0.0002449082,0.0000402664,0.00008218953,0.000171391,0.00003584557,0.00006761879],"category_scores_gemma":[0.0001255487,0.0001324849,0.00006720716,0.00004540893,0.00006054989,0.0005369036,0.000006307902,0.0001920729,0.00002058005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003325348,"about_ca_system_score_gemma":0.0001029715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003453463,"about_ca_topic_score_gemma":0.00001406797,"domain_scores_codex":[0.9991877,0.00002489922,0.0004256555,0.0001617704,0.00007693542,0.0001230228],"domain_scores_gemma":[0.9993294,0.00002353675,0.0002241143,0.0001153118,0.0002422036,0.00006538036],"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":[0.00002605153,0.00003593826,0.0009537979,0.000005316863,0.0002888574,0.000003035905,0.0003221043,0.9940099,0.0008474229,0.0007101052,0.00004216196,0.002755351],"study_design_scores_gemma":[0.01034055,0.0004960941,0.006641323,0.0003708705,0.0002661767,0.01085652,0.006000966,0.4973287,0.4366876,0.002532264,0.0260308,0.002448143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316317,0.0002570539,0.05658859,0.0005773411,0.009517992,0.0001099716,0.00001158592,0.00008305396,0.001222755],"genre_scores_gemma":[0.8350134,0.0002504542,0.1637694,0.00002624653,0.0008171666,0.000002279882,0.000002666224,0.00002832697,0.00008999612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4966811,"threshold_uncertainty_score":0.5402579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585667189638931,"score_gpt":0.2215979080474896,"score_spread":0.2057412361511003,"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."}}