{"id":"W2949203745","doi":"10.1016/j.ejor.2019.10.010","title":"A concise guide to existing and emerging vehicle routing problem variants","year":2019,"lang":"en","type":"preprint","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Vehicle routing problem; Computer science; Diversity (politics); Focus (optics); Routing (electronic design automation); Data science; Management science; Operations research; Risk analysis (engineering); Engineering; Business; Political science; 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":[0.01613283,0.0002316449,0.0003695606,0.0005344868,0.0002432204,0.0005813545,0.0005687333,0.00007022398,0.00007967696],"category_scores_gemma":[0.00262533,0.0002326355,0.00007628782,0.0003349186,0.00004605945,0.0002160165,0.0008528784,0.001827957,0.00007401075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002431862,"about_ca_system_score_gemma":0.0003527554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006613531,"about_ca_topic_score_gemma":7.147982e-7,"domain_scores_codex":[0.9953347,0.001699807,0.001080751,0.0003223651,0.001112348,0.0004499797],"domain_scores_gemma":[0.997101,0.0005473056,0.0001763649,0.0002884651,0.001591548,0.0002952786],"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":[0.00002398655,0.00001359791,0.0005760844,0.0001527521,0.00007595085,0.000122664,0.001483071,0.9764131,0.00738618,0.000379897,0.003750951,0.009621738],"study_design_scores_gemma":[0.001095691,0.0002214494,0.006882154,0.002107793,0.0000273465,0.000191839,0.0004712143,0.9752797,0.0008450695,0.0001226536,0.01221558,0.0005394758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3098083,0.001235704,0.5884961,0.002196527,0.001278681,0.001146345,0.00003982285,0.000151104,0.09564738],"genre_scores_gemma":[0.6599424,0.000117788,0.3378291,0.0000894871,0.0008302507,0.000004541734,0.000008465509,0.0001321737,0.001045723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3501341,"threshold_uncertainty_score":0.9486599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1025177421237348,"score_gpt":0.4009616131474801,"score_spread":0.2984438710237454,"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."}}