{"id":"W7014241079","doi":"","title":"Obtaining optimal and approximate solutions to the problem of scheduling inbound and outbound trucks in cross docking operations","year":2009,"lang":"en","type":"article","venue":"Borås Academic Digital Archive (University of Borås)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wilfrid Laurier University","keywords":"Truck; Heuristic; Scheduling (production processes); Job shop scheduling; Mathematical model; Integer programming; Vehicle routing problem","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001435763,0.001218007,0.001146664,0.0009516993,0.0006651062,0.002025121,0.0009693626,0.001777182,0.004149182],"category_scores_gemma":[0.005946016,0.0007824614,0.0009910823,0.001390943,0.0006328177,0.001378898,0.0008435023,0.001137472,0.0006528974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931115,"about_ca_system_score_gemma":0.003111759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01005768,"about_ca_topic_score_gemma":0.009896494,"domain_scores_codex":[0.9993759,0.000193295,0.00003591818,0.0001128304,0.0001556189,0.0001265574],"domain_scores_gemma":[0.9983163,0.001166945,0.0001729376,0.00008223303,0.0002010256,0.00006068702],"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":[0.00004368795,0.00004238741,0.0002867656,0.00008709093,0.00001918341,0.00002457211,0.00005242054,0.975938,0.000492727,0.008191507,0.0005823349,0.01423934],"study_design_scores_gemma":[0.000008999543,0.00003102606,0.00009432686,0.00001306205,0.000007087081,0.000007128912,0.00005833642,0.9948719,0.0002915667,0.004130865,0.0004812223,0.000004326231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.147396,0.0008495586,0.8300763,0.0004467114,0.0001038069,0.000176216,0.0003206456,0.0003784255,0.02025245],"genre_scores_gemma":[0.5240659,0.001060871,0.4674461,0.0001312216,0.00005470828,0.0004145205,0.0006533664,0.0001762186,0.005997163],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01005768,"threshold_uncertainty_score":0.01999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645139821972165,"score_gpt":0.2444850269484162,"score_spread":0.2280336287286945,"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."}}