{"id":"W2119223389","doi":"10.1080/00207541003690116","title":"A bilinear programming model and a modified branch-and-bound algorithm for production planning in steel rolling mills with substitutable demand","year":2010,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Bilinear interpolation; Sizing; Branch and bound; Production (economics); Production planning; Curse of dimensionality; Integer programming; Linear programming; Integer (computer science); Schedule; Process (computing); Computer science; Algorithm; Mathematics; Economics","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":[0.00169049,0.0008980766,0.001223726,0.0004937775,0.0006175301,0.00139222,0.001470938,0.001159849,0.004374176],"category_scores_gemma":[0.002964346,0.0009069212,0.0007831898,0.001166216,0.000742111,0.001856175,0.001570389,0.00201062,0.0006364735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002544,"about_ca_system_score_gemma":0.001955124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005562501,"about_ca_topic_score_gemma":0.004465899,"domain_scores_codex":[0.9993169,0.0003112238,0.00002522619,0.00009957749,0.0001544538,0.00009250626],"domain_scores_gemma":[0.9988226,0.0008155223,0.00009336438,0.00006258601,0.0001341383,0.00007170275],"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":[0.00007935423,0.00005769615,0.0001306505,0.00005606136,0.0000124118,0.00004171581,0.00004224995,0.9562261,0.0007490037,0.01778345,0.0005579891,0.02426325],"study_design_scores_gemma":[0.000005917024,0.00001619885,0.0000104604,0.000001755007,0.000001592445,0.000004265069,0.000003954578,0.9966136,0.0001122168,0.003013201,0.0002148581,0.000001919804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007960613,0.00009680563,0.9898667,0.0001282872,0.00002216299,0.00003854395,0.00002657054,0.0001661405,0.00169416],"genre_scores_gemma":[0.3140545,0.0002977134,0.6807764,0.0001027196,0.00004375305,0.000283371,0.0001645846,0.000126979,0.004149994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005562501,"threshold_uncertainty_score":0.01463306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07658047894423728,"score_gpt":0.3466042592072398,"score_spread":0.2700237802630026,"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."}}