{"id":"W2891416252","doi":"10.1007/978-981-13-0860-4_19","title":"Ant Colony Algorithm for Routing Alternate Fuel Vehicles in Multi-depot Vehicle Routing Problem","year":2018,"lang":"en","type":"book-chapter","venue":"Asset analytics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Vehicle routing problem; Ant colony optimization algorithms; Mathematical optimization; Constraint (computer-aided design); Ant colony; Routing (electronic design automation); Metaheuristic; Engineering; Operations research; Computer science; Mathematics; Computer network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002543493,0.0008658041,0.0009065463,0.000408863,0.0003894134,0.0008122448,0.001145762,0.0008874692,0.002613325],"category_scores_gemma":[0.0007864265,0.0003452945,0.0005072042,0.0009270546,0.000371313,0.0007539507,0.0006792879,0.001257451,0.0005096916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005234855,"about_ca_system_score_gemma":0.0007608185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006050509,"about_ca_topic_score_gemma":0.004692567,"domain_scores_codex":[0.9998311,0.00005061632,0.000006476504,0.00003447601,0.00005732906,0.00002005343],"domain_scores_gemma":[0.9998121,0.00009658052,0.00001718357,0.00001339826,0.00004780676,0.00001299521],"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":[0.00003538044,0.00003387151,0.0001792353,0.00009051745,0.00002756751,0.00005448506,0.00003942647,0.9147124,0.0009926953,0.01584316,0.006505669,0.06148568],"study_design_scores_gemma":[0.000003703186,0.000007816293,0.00003056647,0.000005042566,0.000003477362,0.00001298655,0.000008488375,0.9936745,0.0001182755,0.004831725,0.001301255,0.000002203816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01206963,0.001524423,0.9712423,0.000428732,0.0002805832,0.00005636627,0.00009684156,0.0002647664,0.01403636],"genre_scores_gemma":[0.3642291,0.002856554,0.603195,0.0002223622,0.0001749223,0.0002918077,0.0004169029,0.0002513314,0.02836192],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006050509,"threshold_uncertainty_score":0.01203054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187281153689133,"score_gpt":0.2958504325081746,"score_spread":0.2539776209712833,"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."}}