{"id":"W4379644131","doi":"10.1016/j.cor.2023.106246","title":"Heterogeneous instant delivery orders scheduling and routing problem","year":2023,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"National Natural Science Foundation of China","keywords":"Instant; Computer science; Mathematical optimization; Column generation; Scheduling (production processes); Job shop scheduling; Integer programming; Vehicle routing problem; Heuristic; Routing (electronic design automation); Algorithm; Mathematics; Computer network","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":[0.001301008,0.000124044,0.0001362629,0.0004539624,0.0005808806,0.0003579767,0.0001992952,0.00007458126,0.00001298935],"category_scores_gemma":[0.0001200778,0.0001359744,0.00002689529,0.001302352,0.00008151685,0.0001950224,0.000227138,0.0003649318,0.00007328663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001019556,"about_ca_system_score_gemma":0.00008064458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004461106,"about_ca_topic_score_gemma":0.00002945832,"domain_scores_codex":[0.9984515,0.0002259297,0.0002548577,0.000274904,0.0003131467,0.000479655],"domain_scores_gemma":[0.9991585,0.0002541249,0.000006854953,0.0002347244,0.0002237133,0.0001220743],"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":[0.000001726043,0.000006249894,0.0001513036,0.00003400987,0.00002301651,0.00001290606,0.0006308054,0.981333,0.002665573,0.000666975,0.0001543166,0.0143201],"study_design_scores_gemma":[0.0002081359,0.00002630382,0.0001406945,0.00005585572,0.000002628471,0.00001334668,0.0001816392,0.9977626,0.0009150088,0.00003001955,0.0005244305,0.000139341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6535938,0.0001698087,0.3440459,0.0003034443,0.0001467861,0.0003723637,0.000004289795,0.0007763301,0.0005872315],"genre_scores_gemma":[0.7827651,0.0001852379,0.2167984,0.00002495368,0.00006044664,0.00003727198,0.00002053932,0.00004314279,0.00006491724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1291712,"threshold_uncertainty_score":0.5544875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0665305166915655,"score_gpt":0.3491616430742612,"score_spread":0.2826311263826957,"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."}}