{"id":"W2065073968","doi":"10.5539/mas.v7n6p90","title":"On Solving Linear Fractional Programming Problems","year":2013,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"VIT University","keywords":"Fractional programming; Linear programming; Simplex algorithm; Decomposition method (queueing theory); Linear-fractional programming; Mathematical optimization; Decomposition; Mathematics; Computer science; Fuzzy logic; Algorithm; Nonlinear programming; Nonlinear system; Discrete mathematics; Artificial intelligence","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":[0.001283322,0.001136853,0.001351359,0.0008839003,0.0007174604,0.00108146,0.0008643389,0.0008965458,0.003273973],"category_scores_gemma":[0.001912685,0.0002990022,0.001154944,0.001481253,0.0007939258,0.001412809,0.001304758,0.001885892,0.0007353503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373619,"about_ca_system_score_gemma":0.0009138563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380374,"about_ca_topic_score_gemma":0.0008548871,"domain_scores_codex":[0.998962,0.0004052621,0.00004168019,0.0001231729,0.0004150497,0.00005282646],"domain_scores_gemma":[0.9996471,0.0001911401,0.00002572202,0.00003133767,0.00009216383,0.00001253682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001067353,0.00009741346,0.0003628081,0.001375202,0.0001228686,0.0002927769,0.0003681692,0.3532469,0.02325931,0.2553279,0.005466693,0.3599733],"study_design_scores_gemma":[0.00003081012,0.00009286141,0.0001464418,0.00009339188,0.00003264642,0.0002159986,0.00005379765,0.9090177,0.005778089,0.06394226,0.02056173,0.00003423039],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001503683,0.000588815,0.9935532,0.00008158322,0.00004806373,0.00002782323,0.00001293639,0.00005492674,0.00412903],"genre_scores_gemma":[0.1206991,0.004435597,0.8634834,0.0002100243,0.0002831171,0.0003925476,0.0001737122,0.0001351352,0.01018736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003273973,"threshold_uncertainty_score":0.01095247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.013430967590886,"score_gpt":0.2232066346652236,"score_spread":0.2097756670743376,"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."}}