{"id":"W2518439593","doi":"10.1016/j.ifacol.2016.07.620","title":"Production Policy Optimization in Flexible Manufacturing-Remanufacturing Systems","year":2016,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Remanufacturing; Production (economics); Mathematical optimization; Computer science; Heuristics; Constraint (computer-aided design); Process (computing); Flexible manufacturing system; Industrial engineering; Manufacturing engineering; Engineering; Mathematics; Economics; Mechanical engineering; Scheduling (production processes)","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":[0.001633839,0.0009949413,0.001075644,0.0006930821,0.0007100219,0.001324588,0.0008965231,0.001227331,0.002214062],"category_scores_gemma":[0.003450532,0.0006368461,0.0006228238,0.0009056925,0.001234484,0.00081271,0.001041577,0.0007065419,0.0001630491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002010269,"about_ca_system_score_gemma":0.00125001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01238931,"about_ca_topic_score_gemma":0.006181672,"domain_scores_codex":[0.9991919,0.000360875,0.00002871937,0.00010788,0.00010064,0.0002100013],"domain_scores_gemma":[0.9978477,0.001602992,0.0002779785,0.00005391877,0.0001202198,0.00009713741],"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":[0.00003084234,0.00001101957,0.0001602678,0.00002409711,0.00001196132,0.00006131083,0.00002165705,0.9931688,0.0003443628,0.004653665,0.00007098208,0.001441026],"study_design_scores_gemma":[0.00001104578,0.00002577734,0.0001142462,0.000004747614,0.000004672062,0.000008083877,0.0000153068,0.9961398,0.0001649461,0.003370708,0.0001363902,0.00000429338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.273701,0.001564889,0.710743,0.0008573887,0.00006779608,0.0001592162,0.0002536462,0.0002469319,0.01240607],"genre_scores_gemma":[0.9839765,0.0002772537,0.01362706,0.00003475772,0.000008859891,0.00006196487,0.00004282678,0.00001788096,0.001952764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01238931,"threshold_uncertainty_score":0.02463436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186920222232908,"score_gpt":0.2218893834804473,"score_spread":0.2100201812581182,"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."}}