{"id":"W2766561679","doi":"10.5539/jms.v7n4p89","title":"A Vehicle Routing Problem with Consideration of Green Transportation","year":2017,"lang":"en","type":"article","venue":"Journal of Management and Sustainability","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan","keywords":"Fuel efficiency; Vehicle routing problem; Terrain; Routing (electronic design automation); Situated; Service (business); Consumption (sociology); Transport engineering; Operations research; Computer science; Genetic algorithm; Automotive engineering; Environmental economics; Business; Engineering; Computer network; Economics","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":[0.001110143,0.001411835,0.001441146,0.0008439143,0.0008094874,0.001682659,0.00140081,0.002361822,0.002636723],"category_scores_gemma":[0.002220321,0.0006373167,0.001389481,0.001549977,0.0008312949,0.002048316,0.00106812,0.001092611,0.0002291986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001800247,"about_ca_system_score_gemma":0.001848037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00664015,"about_ca_topic_score_gemma":0.004648177,"domain_scores_codex":[0.9989348,0.0004566015,0.00003308298,0.0002682236,0.0001357713,0.0001714605],"domain_scores_gemma":[0.9992383,0.0004729333,0.00009749296,0.00003462865,0.00008854498,0.00006827559],"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":[0.00005452797,0.00004268157,0.0003705343,0.0001233917,0.00005369012,0.0001977102,0.00004792854,0.9559997,0.0008134688,0.02956813,0.001139688,0.01158842],"study_design_scores_gemma":[0.00001981256,0.00005818129,0.0001715543,0.0000112164,0.00002873549,0.00007536826,0.00004942847,0.9762323,0.0002661808,0.02049048,0.002584129,0.00001262769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07092025,0.001240483,0.9126316,0.001242623,0.0002615874,0.0001808741,0.0004002064,0.0001491276,0.01297313],"genre_scores_gemma":[0.7751827,0.001435432,0.2065795,0.0002468186,0.000254205,0.0003177783,0.0005494255,0.0001089708,0.01532519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00664015,"threshold_uncertainty_score":0.01320297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009895738117435464,"score_gpt":0.251584277456738,"score_spread":0.2416885393393025,"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."}}