{"id":"W4400338818","doi":"10.1016/j.cor.2024.106761","title":"An exact algorithm for simultaneous pickup and delivery problem with split demand and time windows","year":2024,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Column generation; Pickup; Computer science; Vehicle routing problem; Mathematical optimization; Solver; Algorithm; Heuristic; Routing (electronic design automation); Mathematics; Artificial intelligence","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":[0.0007634969,0.0001288501,0.0001384565,0.0002337688,0.0003059869,0.0007392406,0.0001154711,0.00006651859,0.00001330091],"category_scores_gemma":[0.00002740002,0.0001157898,0.00001426851,0.000327596,0.00009764409,0.0003127453,0.00005275906,0.0002297078,0.000009237903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006018004,"about_ca_system_score_gemma":0.00006974197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001812897,"about_ca_topic_score_gemma":0.00001145058,"domain_scores_codex":[0.9988984,0.0001395254,0.0001564123,0.0003245769,0.0001909341,0.0002901051],"domain_scores_gemma":[0.9988144,0.0006538595,0.00000356637,0.0001847353,0.0002022518,0.000141178],"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":[0.000005505773,0.00001256963,0.00001167725,0.00008932317,0.00003973705,0.00001674659,0.0006054236,0.7979921,0.001269251,0.000172193,0.0002386663,0.1995468],"study_design_scores_gemma":[0.0002770613,0.0002374466,0.00003884339,0.0000859603,0.00001093637,0.00005015692,0.00004351165,0.997668,0.0002719069,0.00003791275,0.001133126,0.0001451298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0647748,0.0006437085,0.9332635,0.0001235536,0.00004668409,0.0007530965,0.00002363908,0.0002644335,0.0001065449],"genre_scores_gemma":[0.1974639,0.00009978477,0.8018357,0.00001622735,0.0001219364,0.00007994643,0.00004030181,0.00005206667,0.0002901922],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1996759,"threshold_uncertainty_score":0.7128514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02498626495706781,"score_gpt":0.3248588548248256,"score_spread":0.2998725898677578,"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."}}