{"id":"W4402125184","doi":"10.1287/ijoc.2023.0404","title":"The Electric Vehicle Routing and Overnight Charging Scheduling Problem on a Multigraph","year":2024,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Multigraph; Vehicle routing problem; Scheduling (production processes); Computer science; Parallel computing; Operations research; Mathematical optimization; Routing (electronic design automation); Mathematics; Computer network; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002010701,0.0002355349,0.0001857369,0.0002934167,0.0008887534,0.001137151,0.0002030475,0.00008402823,0.000003834177],"category_scores_gemma":[0.0002205686,0.0001619112,0.00009925112,0.0006182013,0.00002249229,0.0002998072,0.00004895744,0.001251953,0.00002297932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001693218,"about_ca_system_score_gemma":0.00004063236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001749567,"about_ca_topic_score_gemma":4.238628e-7,"domain_scores_codex":[0.9982998,0.00005824677,0.0005642548,0.0001760304,0.0003567338,0.000544903],"domain_scores_gemma":[0.9986295,0.0009225819,0.0001131522,0.0001397312,0.00006193086,0.0001330794],"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":[0.000009190151,0.000004750941,0.0004308469,0.0000473063,0.00006554928,0.00002169227,0.0008348248,0.7121342,0.001071873,0.002607113,0.00004688021,0.2827258],"study_design_scores_gemma":[0.0002643511,0.00006961958,0.0006514183,0.0007210697,0.00001076175,0.0001718802,0.0001092674,0.9946045,0.001125621,0.0002259853,0.001833643,0.0002119387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8208923,0.001873731,0.1702815,0.0003836116,0.001139667,0.000224613,9.025213e-7,0.0008614266,0.004342228],"genre_scores_gemma":[0.9784905,0.0002410251,0.02055304,0.0001382578,0.0004802873,0.000001926311,5.498002e-7,0.00005896,0.00003540803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2825138,"threshold_uncertainty_score":0.9998997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01068219619837272,"score_gpt":0.2540957879198738,"score_spread":0.243413591721501,"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."}}