{"id":"W4283521573","doi":"10.1007/s10845-022-01969-2","title":"The integrated process planning and scheduling of flexible job-shop-type remanufacturing systems using improved artificial bee colony algorithm","year":2022,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Chinese Government Scholarship; Natural Sciences and Engineering Research Council of Canada","keywords":"Remanufacturing; Job shop scheduling; Workstation; Crossover; Computer science; Scheduling (production processes); Artificial bee colony algorithm; Job shop; Population; Mathematical optimization; Engineering; Flow shop scheduling; Algorithm; Schedule; Artificial intelligence; Manufacturing engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002429742,0.0003466321,0.0005256267,0.0008461794,0.001087833,0.0006546504,0.0007077117,0.00006931921,0.00007274204],"category_scores_gemma":[0.0002142793,0.0002755483,0.0001572647,0.0005114841,0.00009981605,0.0008421221,0.0006639291,0.0007940772,0.000002294521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003911195,"about_ca_system_score_gemma":0.0001181969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003660936,"about_ca_topic_score_gemma":0.000005618183,"domain_scores_codex":[0.9968841,0.00007339731,0.001319832,0.00032449,0.0008007297,0.0005974154],"domain_scores_gemma":[0.9971845,0.00021357,0.001783524,0.0002436082,0.0005302865,0.00004457818],"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":[0.0009673174,0.0001764239,0.001871099,0.001232117,0.0007238308,0.0003286593,0.001711556,0.9564499,0.005065565,0.001201568,0.0002800678,0.02999195],"study_design_scores_gemma":[0.001178813,0.0003452601,0.0007973788,0.0009637787,0.0006520439,0.0003355302,0.1967924,0.6766013,0.08993255,0.003957015,0.0272739,0.001170011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765859,0.001950272,0.01815317,0.000214772,0.00221509,0.0006222852,0.000002216073,0.00005619912,0.0002000855],"genre_scores_gemma":[0.9977392,0.00004114314,0.0009451873,0.0001086186,0.0009094116,0.00001632875,0.000004002505,0.00006389186,0.0001722259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2798485,"threshold_uncertainty_score":0.9999697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02756533239717091,"score_gpt":0.2674589352937918,"score_spread":0.2398936028966209,"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."}}