{"id":"W2282607975","doi":"10.4230/lipics.fsttcs.2012.325","title":"k-delivery traveling salesman problem on tree networks","year":2012,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Travelling salesman problem; Pickup; Routing (electronic design automation); Vehicle routing problem; Tree (set theory); Traveling purchaser problem; Computer science; Mathematical optimization; Mathematics; Combinatorics; 2-opt; Artificial intelligence; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009957608,0.0004825711,0.0004576209,0.00021768,0.0002577033,0.0001742878,0.0004295734,0.0003462289,0.00004629801],"category_scores_gemma":[0.00006015893,0.0004762649,0.0002298415,0.0003286828,0.00005841854,0.001061771,0.00009434028,0.0006202927,0.0001569739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000201896,"about_ca_system_score_gemma":0.00002012394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002800638,"about_ca_topic_score_gemma":0.000003716283,"domain_scores_codex":[0.9971712,0.00005166921,0.001091265,0.0001720241,0.0003661378,0.001147695],"domain_scores_gemma":[0.9985898,0.0002212548,0.0002080318,0.0005294406,0.0001313351,0.0003202089],"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":[0.0001029165,0.0002669533,0.0115639,0.0008325771,0.0003306369,0.000001921975,0.008492725,0.9076936,0.0001022231,0.003215156,0.006454423,0.06094299],"study_design_scores_gemma":[0.001844731,0.0001116083,0.001564654,0.000222758,0.00006553464,0.00002709849,0.00053163,0.9701001,0.000753536,0.00005825718,0.02399313,0.0007269623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1869998,0.0001893213,0.7749764,0.00006941987,0.002199436,0.001486522,0.0001679696,0.001377453,0.03253371],"genre_scores_gemma":[0.8668713,0.00009301674,0.1311346,0.0004406969,0.0006104598,0.000116404,0.0003699333,0.0001669664,0.0001966583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6798716,"threshold_uncertainty_score":0.9997689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01701354244161174,"score_gpt":0.2445203401976485,"score_spread":0.2275067977560368,"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."}}