{"id":"W4408896392","doi":"10.18280/jesa.580201","title":"A Hybrid Memetic and Set Partitioning Optimization Framework for Decision Support in Industrial Transportation: A Case Study of Employee Shuttle Routing","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Memetic algorithm; Vehicle routing problem; Set (abstract data type); Routing (electronic design automation); Computer science; Operations research; Mathematical optimization; Local search (optimization); Engineering; Artificial intelligence; Mathematics; 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":[0.001792657,0.0009274221,0.0008826181,0.001037458,0.0007990965,0.001333951,0.00144665,0.001790077,0.002240443],"category_scores_gemma":[0.0018373,0.0004090795,0.0007019098,0.001212139,0.0006966064,0.0008364326,0.000842365,0.0009284743,0.0001586473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001454208,"about_ca_system_score_gemma":0.001929461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008578925,"about_ca_topic_score_gemma":0.01004457,"domain_scores_codex":[0.9993541,0.0003742904,0.00001824141,0.00006244452,0.0001081352,0.0000827781],"domain_scores_gemma":[0.9990768,0.0006960277,0.00005844549,0.00004038468,0.00007342279,0.0000549053],"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":[0.00004322462,0.00009137057,0.0002699641,0.00005220283,0.00002658389,0.00008865091,0.00004181929,0.9766904,0.0005757821,0.00643205,0.0005242417,0.01516372],"study_design_scores_gemma":[0.00001597865,0.00003796195,0.00007547741,0.000005803842,0.000006834086,0.00002124942,0.00002974236,0.9970301,0.0002688663,0.001753021,0.0007502826,0.000004695646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1989639,0.00116639,0.781485,0.001358368,0.00009746654,0.0003798915,0.000250582,0.0005360267,0.01576239],"genre_scores_gemma":[0.647208,0.000411873,0.3482966,0.0001525588,0.00003417386,0.0003191063,0.0001149669,0.00004808375,0.003414601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008578925,"threshold_uncertainty_score":0.01705796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0307510071816855,"score_gpt":0.2890708148361836,"score_spread":0.2583198076544981,"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."}}