{"id":"W3046352921","doi":"10.1155/2020/8815983","title":"A Fissile Ripple Spreading Algorithm to Solve Time-Dependent Vehicle Routing Problem via Coevolutionary Path Optimization","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematical optimization; Shortest path problem; Computer science; Constrained Shortest Path First; Routing (electronic design automation); Path (computing); Vehicle routing problem; Trajectory; Traffic congestion; Engineering; Computer network; Mathematics; Transport engineering; K shortest path routing","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":[0.0006338421,0.000754561,0.0006560717,0.0006700631,0.000438883,0.000620892,0.0009296551,0.001038912,0.001495564],"category_scores_gemma":[0.001433512,0.0003148138,0.0006841,0.0006571762,0.0005049586,0.0006492275,0.000926681,0.0008944989,0.0001907803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005062572,"about_ca_system_score_gemma":0.001142241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007653294,"about_ca_topic_score_gemma":0.005149527,"domain_scores_codex":[0.9997745,0.0000718508,0.00001194067,0.00004283007,0.00006347798,0.00003541715],"domain_scores_gemma":[0.9996367,0.0002017889,0.00002827402,0.00002310151,0.00008551338,0.00002463772],"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":[0.0000312381,0.0000331005,0.0007156963,0.00003952682,0.00004815557,0.00006060903,0.00006820113,0.9472151,0.001877792,0.00840108,0.0006905984,0.04081902],"study_design_scores_gemma":[0.000003979471,0.00001322117,0.00003865021,0.000001977152,0.000003856484,0.000007873802,0.00000444256,0.9987153,0.0001353591,0.0008570338,0.0002160537,0.000002269381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02922629,0.0003041861,0.9667399,0.0001554825,0.00003997107,0.00005223372,0.00001848313,0.0001447141,0.003318725],"genre_scores_gemma":[0.6747801,0.0004983888,0.318168,0.0001808148,0.00003814001,0.0003534591,0.0001351329,0.00007013035,0.005775845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007653294,"threshold_uncertainty_score":0.01521748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007878574087836812,"score_gpt":0.2298517935174723,"score_spread":0.2219732194296355,"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."}}