{"id":"W2171349556","doi":"10.1504/ijstl.2010.033508","title":"An airfreight forwarder's shipment planning: simultaneous decisions on job, route and agent selection","year":2010,"lang":"en","type":"article","venue":"International Journal of Shipping and Transport Logistics","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Selection (genetic algorithm); Profit (economics); Variety (cybernetics); Computer science; Plan (archaeology); Forwarder; Operations research; Business; Destinations; Function (biology); Operations management; Microeconomics; Tourism; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002609397,0.001131421,0.001258678,0.0005738239,0.0007464528,0.001658621,0.0009843123,0.001683794,0.003940616],"category_scores_gemma":[0.004025211,0.0009053517,0.0007966848,0.0007566596,0.001084984,0.00146846,0.0008816049,0.0008901639,0.0003371581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227934,"about_ca_system_score_gemma":0.001894214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0129301,"about_ca_topic_score_gemma":0.01162917,"domain_scores_codex":[0.9990473,0.0005846948,0.00002281088,0.0001075593,0.00006502077,0.0001724548],"domain_scores_gemma":[0.9979038,0.001510317,0.0002525673,0.00003361284,0.0001008012,0.0001989313],"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":[0.0002540338,0.0000711529,0.0009038643,0.00005703583,0.00003376939,0.0001897937,0.00008158061,0.9874685,0.001148829,0.003359584,0.0002601399,0.006171633],"study_design_scores_gemma":[0.00005931326,0.0002125772,0.00060527,0.000008609916,0.00003314321,0.00002948608,0.0001128668,0.9959189,0.0005622376,0.002084266,0.0003576181,0.00001566696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5998675,0.0005332257,0.3858775,0.001173977,0.00007686592,0.0004112626,0.0001848966,0.0001944959,0.01168022],"genre_scores_gemma":[0.9298912,0.0002575418,0.06509883,0.00007218913,0.00002747039,0.0001726338,0.0000709877,0.00003204192,0.004377135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0129301,"threshold_uncertainty_score":0.02570969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02713762668147851,"score_gpt":0.3018340462913174,"score_spread":0.2746964196098389,"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."}}