{"id":"W2886796913","doi":"10.1155/2018/4805250","title":"A Simulation-Based Dynamic Programming Method for Interchange Scheduling of Port Collecting and Distributing Network","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dalian University of Technology; National Natural Science Foundation of China","keywords":"Port (circuit theory); Computer science; Scheduling (production processes); Intersection (aeronautics); Operations research; Flow network; Traffic simulation; Simulation modeling; Network model; Traffic congestion; Dynamic programming; Mathematical optimization; Simulation; Transport engineering; Engineering; Data mining; Algorithm","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":[0.00112046,0.00007716866,0.0001924638,0.0001042015,0.0003319728,0.00002180647,0.00005697195,0.00006377338,0.000005171101],"category_scores_gemma":[0.0004257935,0.00007991215,0.00007424154,0.0003810804,0.00007334157,0.0002880675,4.92077e-7,0.00008414844,4.11615e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004534097,"about_ca_system_score_gemma":0.000144326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003159086,"about_ca_topic_score_gemma":0.0007942972,"domain_scores_codex":[0.9988975,0.00005385555,0.0005540646,0.0001081644,0.0002169065,0.0001695084],"domain_scores_gemma":[0.9975174,0.0007741263,0.0007797612,0.00003625533,0.0008317626,0.00006067859],"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":[0.000246184,0.0000211458,0.01060002,0.0000515519,0.00002104089,0.000001071925,0.01160318,0.9555004,0.0002218789,0.0003017262,8.035259e-7,0.021431],"study_design_scores_gemma":[0.005803572,0.001670814,0.1370992,0.001997015,0.0005922944,0.000001826426,0.03288832,0.8108901,0.001376497,0.002942348,0.004128143,0.000609934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2698194,0.00007365668,0.7295758,0.0001020549,0.0001876915,0.0002056334,0.00001070629,0.0000154781,0.000009596632],"genre_scores_gemma":[0.619095,0.000007480749,0.380732,0.00001289417,0.0001026214,0.000003614685,0.00003404424,0.000006953542,0.00000543177],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3492756,"threshold_uncertainty_score":0.3258723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02453397377602992,"score_gpt":0.3675801856748105,"score_spread":0.3430462118987806,"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."}}