{"id":"W2899182135","doi":"10.5267/j.ijiec.2018.6.003","title":"A mixed integer linear programming formulation for the vehicle routing problem with backhauls","year":2018,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vehicle routing problem; Integer programming; Mathematical optimization; Linear programming; Mathematics; Integer (computer science); Computer science; Routing (electronic design automation); Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006879057,0.0001520599,0.0001689323,0.0002278915,0.0001111355,0.0001441445,0.0003374197,0.00008925386,0.000008292741],"category_scores_gemma":[0.0004303821,0.000116299,0.00009546364,0.0003291953,0.0000270173,0.0003082781,0.00002816895,0.0003244235,0.000002602213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001572093,"about_ca_system_score_gemma":0.00008334155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004291573,"about_ca_topic_score_gemma":0.000003076281,"domain_scores_codex":[0.9988066,0.00002616177,0.0005192869,0.00009960331,0.0003474843,0.0002008922],"domain_scores_gemma":[0.9978769,0.0006544142,0.0002242676,0.00009149034,0.00108709,0.00006584229],"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":[0.00004656894,0.00001572414,0.0002318604,0.000005716347,0.0002594492,0.00000198071,0.0003587969,0.9707519,0.0003306607,0.001230236,0.0002269362,0.02654022],"study_design_scores_gemma":[0.001321709,0.0001556565,0.0001628521,0.0001933789,0.00005209744,0.0000617981,0.0001117424,0.9905387,0.001251139,0.00004509231,0.005969662,0.00013615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02935315,0.00002534175,0.9677071,0.0006712615,0.001755691,0.0003170716,0.000008014926,0.0001250795,0.00003731929],"genre_scores_gemma":[0.738929,0.000002512318,0.2591462,0.00001704304,0.001831316,0.00001569229,0.000008378766,0.00003891796,0.00001097199],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7095758,"threshold_uncertainty_score":0.4742537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04464265567407138,"score_gpt":0.2932380954278964,"score_spread":0.248595439753825,"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."}}