{"id":"W4366808569","doi":"10.5267/j.jpm.2023.2.001","title":"A robust solution for optimizing facility location and network design with diverse link capacities","year":2023,"lang":"en","type":"article","venue":"Journal of Project Management","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Simulated annealing; Suite; Computer science; Mathematical optimization; Facility location problem; Network planning and design; Heuristic; Robust optimization; Meta heuristic; Algorithm; Mathematics","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":[0.001759347,0.0001731202,0.0002199551,0.0005073816,0.0003102808,0.0001931689,0.000173836,0.00003820234,0.00002192469],"category_scores_gemma":[0.00005419098,0.000143345,0.0000685729,0.0008686897,0.00006948383,0.0009332832,0.0001414243,0.00009477255,0.00003044529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007555183,"about_ca_system_score_gemma":0.00002479007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001488528,"about_ca_topic_score_gemma":0.00008377192,"domain_scores_codex":[0.9986492,0.00002614152,0.0004370327,0.0002229657,0.0003521175,0.0003125663],"domain_scores_gemma":[0.9991608,0.00002975284,0.0002588239,0.0001631395,0.0003718094,0.00001572462],"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":[0.0007435887,0.0001031478,0.0006132583,0.002560666,0.0004613464,0.00002475295,0.0006767712,0.8313095,0.00001987734,0.01151401,0.1070857,0.04488736],"study_design_scores_gemma":[0.003824739,0.0003497139,0.007164517,0.000539377,0.0008823957,0.000007592002,0.01315417,0.7947485,0.00001530013,0.00320609,0.1753672,0.0007403312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007413832,0.0001209905,0.9864563,0.002412702,0.0006788644,0.001682898,0.000003452148,0.0001368049,0.001094174],"genre_scores_gemma":[0.8102646,0.001457125,0.1757704,0.00214218,0.003496215,0.0005522826,0.0001627998,0.00009114424,0.006063196],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8106859,"threshold_uncertainty_score":0.5845438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1070573488500199,"score_gpt":0.2550223557784843,"score_spread":0.1479650069284644,"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."}}