{"id":"W3118945546","doi":"10.1007/s43069-020-00044-x","title":"Branch-and-Price for a Multi-attribute Technician Routing and Scheduling Problem","year":2021,"lang":"en","type":"article","venue":"Operations Research Forum","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Université du Québec à Montréal; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Branch and price; Arc routing; Technician; Column generation; Solver; Mathematical optimization; Integer programming; Scheduling (production processes); Algorithm; Routing (electronic design automation); Mathematics; Engineering; Computer network","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":[],"consensus_categories":[],"category_scores_codex":[0.001405516,0.0001052274,0.0001412426,0.000148666,0.0007093897,0.0003194404,0.00009159516,0.00009422775,0.00001389257],"category_scores_gemma":[0.000971488,0.0001139257,0.00002646807,0.0005558793,0.00005716102,0.0002394506,0.0001445868,0.0003215015,0.000004605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007360305,"about_ca_system_score_gemma":0.0000941519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001756763,"about_ca_topic_score_gemma":0.0001449991,"domain_scores_codex":[0.9987275,0.0001044136,0.0002262526,0.0002631751,0.0001798875,0.0004988004],"domain_scores_gemma":[0.999056,0.0001867021,0.000008101204,0.0001992801,0.0004353691,0.0001145083],"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":[0.000005870209,0.00006396801,0.004415133,0.0002791048,0.00007911006,0.000006324045,0.0009732173,0.8501771,0.1005322,0.01715779,0.0003368355,0.02597334],"study_design_scores_gemma":[0.0004652655,0.00002342381,0.0003654577,0.00006896212,0.000005295811,0.00001595569,0.0005347442,0.9819887,0.01478677,0.00007613596,0.001532365,0.0001369125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04091056,0.0007605418,0.9553169,0.001795931,0.00004643449,0.000608667,0.00002793747,0.0002003837,0.0003326282],"genre_scores_gemma":[0.3859794,0.0001569897,0.6130509,0.00003354175,0.00003665817,0.0001619332,0.0000262541,0.00003544291,0.0005189059],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3450688,"threshold_uncertainty_score":0.5456124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08663084792724975,"score_gpt":0.3906069132587584,"score_spread":0.3039760653315087,"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."}}