{"id":"W4391909353","doi":"10.5267/j.jpm.2024.1.002","title":"Optimization of transport constraints and quality of service for joint resolution of uncertain scheduling and the job-shop problem with routing (JSSPR) as opposed to the job-shop problem with transport (JSSPT)","year":2024,"lang":"en","type":"article","venue":"Journal of Project Management","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Job shop; Job shop scheduling; Operations research; Computer science; Scheduling (production processes); Service quality; Routing (electronic design automation); Operations management; Business; Service (business); Flow shop scheduling; Engineering; Marketing; Computer network","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":[0.001595392,0.0009494197,0.0009209079,0.0006855289,0.000549487,0.001604125,0.001087884,0.001078742,0.003422398],"category_scores_gemma":[0.002635839,0.0005040781,0.001003152,0.001113511,0.0009258316,0.001624815,0.001082367,0.001329881,0.0002477069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001718136,"about_ca_system_score_gemma":0.002051749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005340504,"about_ca_topic_score_gemma":0.003752787,"domain_scores_codex":[0.9988607,0.0004783423,0.00004111986,0.0001710301,0.0002535967,0.0001952357],"domain_scores_gemma":[0.9990206,0.0006361761,0.000126799,0.00003675408,0.00009087825,0.00008875647],"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":[0.00007883301,0.0000458876,0.0002240026,0.0001040756,0.00003285189,0.0001052169,0.000042924,0.9550548,0.002143404,0.02751023,0.000912443,0.01374538],"study_design_scores_gemma":[0.00001370118,0.00005082083,0.0001567021,0.00001128759,0.00001246238,0.00003138074,0.00004171674,0.986568,0.000878584,0.01094635,0.001279898,0.000009062631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06164269,0.00079777,0.9277505,0.0005860007,0.0001096709,0.0001288834,0.0002434326,0.0002005258,0.008540535],"genre_scores_gemma":[0.8041831,0.0008766215,0.1872066,0.0001827283,0.00009718447,0.000205755,0.0004285171,0.0001925132,0.00662687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005340504,"threshold_uncertainty_score":0.01246601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011672270248211,"score_gpt":0.2687513315424775,"score_spread":0.2386346088399954,"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."}}