{"id":"W2789761009","doi":"10.5267/j.dsl.2018.2.002","title":"A stochastic time-dependent green capacitated vehicle routing and scheduling problem with time window, resiliency and reliability: a case study","year":2018,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Tehran","keywords":"Scheduling (production processes); Vehicle routing problem; Reliability (semiconductor); Computer science; Mathematical optimization; Operations research; Reliability engineering; Engineering; Routing (electronic design automation); Mathematics; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003234006,0.0002228416,0.0002500136,0.0003296464,0.0005778481,0.0002944967,0.0002504739,0.00004884669,0.00001316761],"category_scores_gemma":[0.0005481481,0.0001877217,0.00001560197,0.001227441,0.000657018,0.0005165393,0.0001729829,0.0002270879,0.00002924848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046785,"about_ca_system_score_gemma":0.00003987044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001171163,"about_ca_topic_score_gemma":0.00001983223,"domain_scores_codex":[0.9976305,0.0001185111,0.0003926398,0.0006994727,0.0006921371,0.0004667348],"domain_scores_gemma":[0.998621,0.0004524142,0.00008193829,0.0004437295,0.0001868555,0.0002140482],"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":[0.0001070986,0.0000902981,0.01640312,0.00002833266,0.00002875122,0.0005840641,0.01600482,0.7575725,0.1708516,0.000004897736,0.00002156856,0.03830299],"study_design_scores_gemma":[0.0009400186,0.0002671388,0.003074149,0.00009756784,0.00002738006,0.0008101322,0.001065017,0.9927592,0.0006133901,0.00004297917,0.000001830439,0.0003011453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7900748,0.000009262541,0.2090088,0.0001448865,0.00004391066,0.0004769341,0.000001793427,0.0001965854,0.00004305391],"genre_scores_gemma":[0.8661283,3.732989e-7,0.1336557,0.000123155,0.0000347973,0.00001182199,2.571447e-7,0.00002975411,0.00001582371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2351868,"threshold_uncertainty_score":0.7655067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118728620169398,"score_gpt":0.264793870505356,"score_spread":0.2529210084884162,"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."}}