{"id":"W2234524595","doi":"10.1007/978-3-319-24264-4_14","title":"A Matheuristic for the Liner Shipping Network Design Problem with Transit Time Restrictions","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Computer science; Benchmark (surveying); Suite; Transit time; Port (circuit theory); Flow network; Revenue; Transit (satellite); Mathematical optimization; Heuristic; Network planning and design; Operator (biology); Operations research; Integer (computer science); Flow (mathematics); Integer programming; Scale (ratio); Class (philosophy); Transport engineering; Public transport; Algorithm; Telecommunications; Mathematics; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005757342,0.0002748884,0.0002540425,0.0001154302,0.0001842687,0.0001581239,0.0004743254,0.0001487993,0.00002601867],"category_scores_gemma":[0.00002865678,0.0001790632,0.00004474588,0.000208433,0.0002551831,0.00005629492,0.000047978,0.000419657,0.000007629236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009500232,"about_ca_system_score_gemma":0.0001716556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007805657,"about_ca_topic_score_gemma":0.00003054032,"domain_scores_codex":[0.9987407,0.000008522351,0.0002363172,0.0003495494,0.0002840275,0.0003808751],"domain_scores_gemma":[0.9986871,0.0006765959,0.0000563177,0.0003731967,0.0001312211,0.00007554282],"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":[0.00000627839,0.000003025913,0.000001309541,0.00003653015,0.00001315407,0.00001092529,0.0001021608,0.946355,0.000001827164,0.001236468,0.0005110823,0.05172217],"study_design_scores_gemma":[0.0001107895,0.00009741071,0.00000586903,0.0001974414,0.00004626442,0.00003409469,5.769191e-8,0.9437758,0.000004739436,0.04554696,0.009913456,0.0002670992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[4.331286e-7,0.0007763794,0.9949994,0.0001773437,0.0003831689,0.0006587922,0.000009426186,0.0001418457,0.002853185],"genre_scores_gemma":[0.01859687,0.00005559163,0.9778103,0.0002414682,0.001642893,0.00006660945,0.00001383497,0.0001090944,0.001463313],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05145507,"threshold_uncertainty_score":0.7301984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03359554269804536,"score_gpt":0.2199406000792333,"score_spread":0.186345057381188,"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."}}