{"id":"W3117154257","doi":"10.1093/jcde/qwaa089","title":"A biobjective home health care logistics considering the working time and route balancing: a self-adaptive social engineering optimizer","year":2020,"lang":"en","type":"article","venue":"Journal of Computational Design and Engineering","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Metaheuristic; Vehicle routing problem; Scheduling (production processes); Computer science; Population; Operations research; Operations management; Routing (electronic design automation); Engineering; Artificial intelligence; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001161032,0.001256848,0.001206919,0.0008291395,0.0005246414,0.001448735,0.001020562,0.001674843,0.00218221],"category_scores_gemma":[0.002044992,0.0004940063,0.001165756,0.0006159349,0.0006405727,0.0007298312,0.001200634,0.001149913,0.0001966299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009266006,"about_ca_system_score_gemma":0.001403686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006698887,"about_ca_topic_score_gemma":0.002995283,"domain_scores_codex":[0.9994851,0.0002128531,0.00002048815,0.00009089346,0.0001050864,0.00008545567],"domain_scores_gemma":[0.9991561,0.0004972095,0.00009861367,0.00003392371,0.0001515157,0.00006268141],"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":[0.0000248969,0.00005334691,0.0004315012,0.00003800603,0.00003629678,0.00005485916,0.00002104246,0.9894806,0.0004104491,0.003103222,0.0004424226,0.005903341],"study_design_scores_gemma":[0.000004525722,0.00002104717,0.00005873368,0.000004828332,0.000006897776,0.00000541136,0.00001113555,0.9989661,0.00006304138,0.0006500027,0.0002062902,0.000002047154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09556397,0.0008489063,0.88832,0.0009921503,0.0001650656,0.0002235682,0.0001535807,0.0002251726,0.01350767],"genre_scores_gemma":[0.8534458,0.0005349874,0.1391636,0.0003478933,0.00008924709,0.0004456133,0.0001947671,0.00007795726,0.005700063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006698887,"threshold_uncertainty_score":0.01331979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02356356349678254,"score_gpt":0.2333514766491852,"score_spread":0.2097879131524027,"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."}}