{"id":"W4292237905","doi":"10.1016/j.ins.2022.06.052","title":"Multi-objective scheduling of priority-based rescue vehicles to extinguish forest fires using a multi-objective discrete gravitational search algorithm","year":2022,"lang":"en","type":"article","venue":"Information Sciences","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":93,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"National Natural Science Foundation of China","keywords":"Firefighting; Computer science; Scheduling (production processes); Emergency rescue; Multi-objective optimization; Pareto principle; Mathematical optimization; Operations research; Engineering; Mathematics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007708053,0.0007812231,0.001286887,0.0009566721,0.0005782144,0.0008740037,0.001247013,0.001083238,0.001847364],"category_scores_gemma":[0.00134812,0.0004919183,0.0007993493,0.0006623391,0.0005193526,0.0005725056,0.0007859916,0.0006850173,0.0001497093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019884,"about_ca_system_score_gemma":0.001965291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01512102,"about_ca_topic_score_gemma":0.009456345,"domain_scores_codex":[0.9997407,0.00007757651,0.000012882,0.00004818732,0.00006322698,0.00005741453],"domain_scores_gemma":[0.9994609,0.0002826308,0.0000728039,0.00001650779,0.00009154107,0.00007564006],"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":[0.00005833462,0.00005555727,0.000247127,0.00002969949,0.00002699667,0.00002713117,0.00002133695,0.9882408,0.0007602674,0.001241749,0.0002595724,0.00903151],"study_design_scores_gemma":[0.00001494123,0.00002471127,0.00006371478,0.000001409026,0.000005329692,0.000002567155,0.000005368646,0.9995449,0.0000800824,0.0001980027,0.00005713932,0.000001697331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1752924,0.0004325613,0.8166288,0.0003620705,0.0001558968,0.0002186604,0.00009812242,0.0003681239,0.006443455],"genre_scores_gemma":[0.8762556,0.0001491276,0.1209246,0.00008178316,0.00004048101,0.0001601261,0.0001092035,0.00003916488,0.002239878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01512102,"threshold_uncertainty_score":0.03006601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05680309308314085,"score_gpt":0.3180184983496859,"score_spread":0.261215405266545,"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."}}