{"id":"W2730563372","doi":"10.1007/s10479-017-2567-3","title":"A meta-heuristic for capacitated green vehicle routing problem","year":2017,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Vehicle routing problem; Mathematical optimization; Alternative fuel vehicle; Heuristic; Routing (electronic design automation); Ant colony optimization algorithms; Computer science; Ant colony; Engineering; Automotive engineering; Alternative fuels; 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":[0.0009828358,0.001134353,0.001216223,0.001699014,0.0005868221,0.001288357,0.001698055,0.002150411,0.003165476],"category_scores_gemma":[0.001682328,0.0007005589,0.001340224,0.001492865,0.0005362393,0.0007896884,0.0008954275,0.001261673,0.0003700048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001220648,"about_ca_system_score_gemma":0.001456157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004154815,"about_ca_topic_score_gemma":0.003894113,"domain_scores_codex":[0.9996009,0.0001778935,0.00001714936,0.00004805852,0.00008810851,0.00006788632],"domain_scores_gemma":[0.9994604,0.0003149832,0.00004831548,0.00004497819,0.00009190369,0.00003945159],"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":[0.00005476248,0.00007205404,0.0002215561,0.00006552098,0.00005240993,0.00005312745,0.00002437493,0.9625316,0.0007681427,0.006722289,0.001132145,0.02830201],"study_design_scores_gemma":[0.00002138883,0.000037779,0.00005818123,0.00001690044,0.00002408035,0.0000151447,0.00001038117,0.9968072,0.0001962376,0.002164058,0.0006440686,0.000004595253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07389739,0.002147917,0.8991833,0.0007706771,0.0004229964,0.0002802899,0.0002751765,0.0005145141,0.02250775],"genre_scores_gemma":[0.533897,0.0009764299,0.4579318,0.00029042,0.0001605518,0.0005598557,0.0003035352,0.000129921,0.005750398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004154815,"threshold_uncertainty_score":0.0105896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.484601735208781,"score_gpt":0.4827331472826162,"score_spread":0.001868587926164789,"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."}}