{"id":"W3153206778","doi":"10.5267/j.ijiec.2021.1.002","title":"Incorporating batching decisions and operational constraints into the scheduling problem of multisite manufacturing environments","year":2021,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Nacional de Promoción Científica y Tecnológica; Fondo para la Investigación Científica y Tecnológica; Consejo Nacional de Investigaciones Científicas y Técnicas; Universidad Tecnológica Nacional","keywords":"Scheduling (production processes); Standardization; Computer science; Integer programming; Operations research; Production (economics); Batch production; Production planning; Mathematical optimization; Operations management; Engineering; Economics; Mathematics; Microeconomics","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":[0.001915622,0.001512879,0.00148595,0.0004487466,0.0006518079,0.002122876,0.001501514,0.002204593,0.002587225],"category_scores_gemma":[0.003426789,0.0009254025,0.001116794,0.001011397,0.0009789175,0.00177227,0.001101691,0.002723383,0.0002334619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001660382,"about_ca_system_score_gemma":0.001946681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009511886,"about_ca_topic_score_gemma":0.01036891,"domain_scores_codex":[0.9983747,0.0008156842,0.00005659687,0.0002714513,0.0002087374,0.0002727329],"domain_scores_gemma":[0.9965461,0.002698934,0.0002959476,0.00008212018,0.0001778595,0.0001990794],"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":[0.00005766551,0.00005468347,0.0002046566,0.00004022098,0.00001525548,0.0001074716,0.00002326278,0.9882428,0.0007290569,0.006208875,0.0001535165,0.004162568],"study_design_scores_gemma":[0.00001802642,0.00008003179,0.0001709595,0.000007459452,0.00001014384,0.00002268627,0.00002498405,0.9941348,0.0005435857,0.004574138,0.0004021662,0.000010982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1119275,0.0007643236,0.8774066,0.0008063856,0.0001232486,0.0001839453,0.0002031522,0.0001848362,0.008400046],"genre_scores_gemma":[0.8807707,0.0007289692,0.1117514,0.0001362309,0.00009855304,0.0002059384,0.0001675302,0.00007201704,0.006068701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009511886,"threshold_uncertainty_score":0.01891303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848057158205576,"score_gpt":0.2442887631696083,"score_spread":0.2258081915875526,"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."}}