{"id":"W4409284532","doi":"10.1007/s10479-025-06561-4","title":"Two simplex-based approximate stochastic dynamic programming schemes for a real hydropower management problem","year":2025,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Water resources management and optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Rio Tinto (Canada); Université Laval; Laurentian University","funders":"","keywords":"Theory of computation; Mathematical optimization; Stochastic programming; Dynamic programming; Simplex; Computer science; Simplex algorithm; Hydropower; Mathematics; Linear programming; Algorithm; Combinatorics","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":[0.002831734,0.0008603975,0.001530075,0.0007521639,0.0006387465,0.001678141,0.001666871,0.002209135,0.003675564],"category_scores_gemma":[0.006881163,0.0005845836,0.0009782293,0.0009979554,0.001007613,0.001739232,0.001979511,0.002098357,0.0003461354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001551999,"about_ca_system_score_gemma":0.002006131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007262939,"about_ca_topic_score_gemma":0.006131316,"domain_scores_codex":[0.9991143,0.0004826733,0.0000430603,0.00007178583,0.0002083,0.00007971933],"domain_scores_gemma":[0.9973227,0.001680764,0.0001541799,0.0001889923,0.0004635137,0.0001897642],"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":[0.0001358587,0.00007402382,0.0001735691,0.00005643085,0.00002452543,0.00002382233,0.00007856922,0.9501649,0.0005241699,0.02265593,0.000534285,0.02555379],"study_design_scores_gemma":[0.000009056369,0.00001820788,0.00002099175,0.000003509934,0.000002761104,0.000003480647,0.000004360799,0.9979881,0.0000570703,0.001736721,0.0001519924,0.000003757731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02546546,0.0003306178,0.9691536,0.0003439536,0.00009371686,0.0001001868,0.00005611844,0.0001118782,0.004344459],"genre_scores_gemma":[0.5727565,0.0004041809,0.4206387,0.0001574584,0.0000988165,0.0003810606,0.0001336671,0.0001344543,0.005295215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007262939,"threshold_uncertainty_score":0.01497579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06274712068409638,"score_gpt":0.4042494648851683,"score_spread":0.3415023442010719,"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."}}