{"id":"W4413872469","doi":"10.5267/j.ijiec.2025.8.003","title":"An improved adaptive large neighborhood search algorithm on collaborative last mile delivery with roaming customers","year":2025,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Basic and Applied Basic Research Foundation of Guangdong Province","keywords":"Roaming; Mile; Last mile (transportation); Computer science; Algorithm; Mathematical optimization; Transport engineering; Real-time computing; Engineering; Computer network; Mathematics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007851615,0.0006953454,0.001549481,0.0004778716,0.0006137924,0.0006823989,0.001964181,0.001042893,0.002089172],"category_scores_gemma":[0.001309629,0.0004599872,0.0006473742,0.0007110003,0.0003620487,0.0009838139,0.001002532,0.0008170019,0.0003829295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006899277,"about_ca_system_score_gemma":0.001414788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0112691,"about_ca_topic_score_gemma":0.008796308,"domain_scores_codex":[0.9995838,0.0001226469,0.00001609727,0.0001051284,0.00008419313,0.00008816307],"domain_scores_gemma":[0.9995551,0.0002238915,0.00005783275,0.00002932334,0.00008720817,0.00004667098],"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":[0.0001084484,0.00006487616,0.0004658234,0.00003227711,0.00002700369,0.00006017306,0.00004763037,0.9568255,0.0007922725,0.004335319,0.001494432,0.03574616],"study_design_scores_gemma":[0.000007804426,0.0000143214,0.00002741994,0.000001251731,0.000002575031,0.000005859382,0.000005447255,0.9992268,0.00007013134,0.0004480679,0.0001887722,0.000001517885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04601231,0.000416446,0.9487494,0.0002163469,0.00006670181,0.00007616176,0.0000730849,0.0003802888,0.004009254],"genre_scores_gemma":[0.6920006,0.0002059377,0.3015924,0.0001570085,0.00005585018,0.000242614,0.0002715976,0.0001020435,0.005372043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0112691,"threshold_uncertainty_score":0.022407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173676675300361,"score_gpt":0.2376645769144932,"score_spread":0.2202969093844571,"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."}}