{"id":"W4320033621","doi":"10.1016/j.cor.2023.106184","title":"The road train optimization problem with load assignment","year":2023,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Solver; Computer science; Train; Iterated local search; Computation; Vehicle routing problem; Routing (electronic design automation); Set (abstract data type); Mathematical optimization; Iterated function; Trailer; Optimization problem; Algorithm; Local search (optimization); Mathematics; Automotive engineering; Computer network; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008840237,0.0009009328,0.00119491,0.0008351321,0.0005038511,0.001542745,0.001618256,0.001880954,0.01009703],"category_scores_gemma":[0.002849983,0.0006265834,0.000873875,0.00159475,0.0007921121,0.002090491,0.001223035,0.001235456,0.0008226353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222922,"about_ca_system_score_gemma":0.001493295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008757152,"about_ca_topic_score_gemma":0.006868954,"domain_scores_codex":[0.9993124,0.0003411756,0.00001576128,0.0001339923,0.0001039216,0.00009283682],"domain_scores_gemma":[0.9994875,0.0003394289,0.00004762041,0.00003061946,0.00004824786,0.00004648446],"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":[0.00006877409,0.00007497607,0.0002126084,0.00009232791,0.00003442863,0.00005864489,0.0000271265,0.9453545,0.0003510586,0.02707819,0.003960627,0.02268673],"study_design_scores_gemma":[0.00001672636,0.00002179005,0.0001154658,0.000006055294,0.000009533904,0.00001734104,0.00001816223,0.9812105,0.0001442773,0.01641282,0.002021546,0.000005805758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0371746,0.0006485815,0.9282886,0.001383893,0.0001860379,0.0001411222,0.0005002407,0.0002116244,0.03146539],"genre_scores_gemma":[0.6850583,0.00124696,0.2439899,0.0003476339,0.0004377264,0.0003737465,0.000754736,0.0003787386,0.06741223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01009703,"threshold_uncertainty_score":0.03377789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05546643026522786,"score_gpt":0.3473781121769456,"score_spread":0.2919116819117178,"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."}}