{"id":"W2552752966","doi":"10.1016/j.jal.2016.11.010","title":"A survey on the inventory-routing problem with stochastic lead times and demands","year":2016,"lang":"en","type":"article","venue":"Journal of Applied Logic","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Lead time; Operations research; Supply chain; Key (lock); Routing (electronic design automation); Inventory control; Inventory theory; Supply chain management; Control (management); Variable (mathematics); Synchronization (alternating current); Lead (geology); Field (mathematics); Mathematical optimization; Operations management; Economics; Mathematics; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001401781,0.0001161774,0.0001818211,0.00006809439,0.00006090221,0.00003207471,0.0001190244,0.00004736746,0.00002310015],"category_scores_gemma":[0.00009855008,0.00005284509,0.00002221178,0.0001306097,0.00005112706,0.00004575904,0.00001662331,0.0001772546,0.000006218977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004256719,"about_ca_system_score_gemma":0.0000197614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.098676e-7,"about_ca_topic_score_gemma":0.000002438839,"domain_scores_codex":[0.9992626,0.00006586841,0.0002539607,0.00008087361,0.0001778069,0.0001589358],"domain_scores_gemma":[0.9990832,0.0005441178,0.0001587912,0.0001003178,0.00006033912,0.00005322768],"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":[0.0003798603,0.00006366887,0.005181155,0.00006212422,0.0002976625,0.00001498218,0.0010372,0.9435815,0.007725412,0.01474785,0.002009698,0.02489888],"study_design_scores_gemma":[0.01847086,0.004361589,0.1238439,0.004100666,0.0006764737,0.0007240099,0.001749939,0.7751362,0.0165522,0.04967225,0.001152122,0.003559783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3942963,0.0001391136,0.5988532,0.0006573578,0.00008799102,0.000275548,0.000002804979,0.0000977706,0.00558995],"genre_scores_gemma":[0.9872203,0.00001355862,0.0125426,0.00008926188,0.00006316048,0.000003310151,2.300871e-7,0.00002285685,0.00004469121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5929241,"threshold_uncertainty_score":0.215496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02773312998187052,"score_gpt":0.2422598730721083,"score_spread":0.2145267430902378,"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."}}