{"id":"W2065749076","doi":"10.1007/s10696-007-9020-x","title":"Optimal configuration selection for Reconfigurable Manufacturing Systems","year":2007,"lang":"en","type":"article","venue":"International Journal of Flexible Manufacturing Systems","topic":"Flexible and Reconfigurable Manufacturing Systems","field":"Engineering","cited_by":145,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Control reconfiguration; Tabu search; Heuristics; Time horizon; Mathematical optimization; Selection (genetic algorithm); Smoothness; Computer science; Genetic algorithm; Reliability engineering; Engineering; Mathematics","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":[0.0005699774,0.00103794,0.001220633,0.001323015,0.0005899792,0.001015263,0.0007755152,0.0007925421,0.003376755],"category_scores_gemma":[0.001937031,0.0007401226,0.0005529246,0.001112899,0.0007362237,0.0007292635,0.0007418246,0.0004723499,0.0003643019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007477721,"about_ca_system_score_gemma":0.0007750922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740861,"about_ca_topic_score_gemma":0.00190322,"domain_scores_codex":[0.9994258,0.0002040655,0.00002267744,0.00008999588,0.0001348498,0.0001226537],"domain_scores_gemma":[0.9992791,0.0004193586,0.00009625371,0.00005882121,0.00009549728,0.00005098272],"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":[0.0001966355,0.00004768523,0.0003678265,0.00007488272,0.00005386763,0.0001493671,0.00003604303,0.9381254,0.004595041,0.005579737,0.001063987,0.04970953],"study_design_scores_gemma":[0.00005314943,0.0001110645,0.0003751061,0.00001662842,0.00003064321,0.00008403237,0.00002807788,0.9844301,0.002003672,0.01219236,0.0006554054,0.00001976072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.296035,0.001972174,0.6732357,0.000565792,0.0001702311,0.0001705216,0.0001938287,0.000763291,0.02689349],"genre_scores_gemma":[0.9458622,0.0002427684,0.05103736,0.00007584321,0.00002247202,0.00007660833,0.00008717854,0.00006144292,0.002534193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003376755,"threshold_uncertainty_score":0.01129633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582303873096429,"score_gpt":0.2523213226468218,"score_spread":0.2364982839158575,"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."}}