{"id":"W1985043293","doi":"10.1016/j.cor.2009.04.011","title":"An efficient heuristic for reliability design optimization problems","year":2009,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Computer science; Tabu search; Redundancy (engineering); Disjoint sets; Genetic algorithm; Heuristic; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001821212,0.001631885,0.001810749,0.002083276,0.0008209656,0.001234706,0.001744833,0.002199332,0.005876423],"category_scores_gemma":[0.004218507,0.001079677,0.001352559,0.002098983,0.0008463866,0.001235918,0.001289369,0.001655184,0.001025415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001148404,"about_ca_system_score_gemma":0.001874857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003198806,"about_ca_topic_score_gemma":0.004511602,"domain_scores_codex":[0.9991075,0.0003815402,0.00003513959,0.00007672734,0.0002806797,0.0001182694],"domain_scores_gemma":[0.9982871,0.001194609,0.00009905069,0.0001475966,0.0002052768,0.0000663977],"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":[0.0001695929,0.0001622476,0.000192127,0.0001688893,0.00005073918,0.00009338711,0.0000475641,0.8469134,0.001591787,0.01538303,0.004306716,0.1309205],"study_design_scores_gemma":[0.00007901996,0.00005321973,0.00006103336,0.0000229729,0.00002503362,0.00002810901,0.00001053767,0.9884008,0.0003605513,0.008972398,0.001977409,0.000008997134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01261889,0.000988793,0.9731371,0.0002546738,0.0002472723,0.0001913495,0.0001448818,0.0007283216,0.01168869],"genre_scores_gemma":[0.1376271,0.0005465241,0.8564668,0.0002658246,0.0001282408,0.0005442317,0.000258437,0.0002380097,0.003924855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005876423,"threshold_uncertainty_score":0.01965857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04840033153782702,"score_gpt":0.3287658277759168,"score_spread":0.2803654962380898,"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."}}