{"id":"W4206915070","doi":"10.5539/mas.v16n1p30","title":"New Approach to Obtain the Maximum Flow in a Network and Optimal Solution for the Transportation Problems","year":2022,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rajarata University of Sri Lanka","keywords":"Maximum flow problem; Minimum-cost flow problem; Flow network; Out-of-kilter algorithm; Multi-commodity flow problem; Computer science; Mathematical optimization; Flow (mathematics); Heuristic; Algorithm; Mathematics; Theoretical computer science; Graph","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001483312,0.001335257,0.0008244963,0.0020934,0.0007510759,0.001463856,0.001528054,0.001578582,0.005344118],"category_scores_gemma":[0.002971787,0.0006577502,0.00159292,0.001845295,0.001450245,0.00295725,0.001422503,0.002983669,0.0008119224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00157023,"about_ca_system_score_gemma":0.001896311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001932231,"about_ca_topic_score_gemma":0.002375817,"domain_scores_codex":[0.999083,0.0002995287,0.00004629602,0.0001967248,0.0003186575,0.0000557093],"domain_scores_gemma":[0.9995185,0.0002713839,0.00004619811,0.00004088478,0.0001017528,0.0000212511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003159807,0.00007710033,0.0002627962,0.0003416672,0.00005733305,0.0001281412,0.0001855243,0.3180935,0.002976418,0.5809537,0.006792926,0.09009928],"study_design_scores_gemma":[0.00002389977,0.00005828253,0.0001268484,0.00008450816,0.00002483927,0.000176076,0.00005224626,0.7672326,0.001528434,0.2012356,0.0294329,0.00002382283],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008459527,0.0004319208,0.9918513,0.0002728401,0.00008395523,0.00003021123,0.00002317626,0.00004372245,0.006416967],"genre_scores_gemma":[0.03906156,0.001595031,0.9525392,0.0002203579,0.0002384451,0.0002640323,0.00008500237,0.0000947414,0.005901552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005344118,"threshold_uncertainty_score":0.01787788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929774037166811,"score_gpt":0.2154717108606233,"score_spread":0.1961739704889552,"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."}}