{"id":"W1966575776","doi":"10.1016/j.cie.2005.04.001","title":"A neural network to enhance local search in the permutation flowshop","year":2005,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; Toronto Metropolitan University","funders":"","keywords":"Tabu search; Artificial neural network; Heuristics; Permutation (music); Pairwise comparison; Local search (optimization); Local optimum; Sequence (biology); Computer science; Mathematical optimization; Artificial intelligence; Mathematics; Algorithm; Machine learning; Pattern recognition (psychology)","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":[0.0007719028,0.00034737,0.0005903344,0.0003798331,0.0003016234,0.0004075111,0.0008354317,0.0008546395,0.001724027],"category_scores_gemma":[0.002004979,0.0003041391,0.0002119023,0.0004014118,0.0003841866,0.000987328,0.0005835451,0.0006689955,0.0001638467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005051498,"about_ca_system_score_gemma":0.0004680558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004044407,"about_ca_topic_score_gemma":0.005287171,"domain_scores_codex":[0.9998639,0.0000452543,0.000008257754,0.00002514998,0.00003259576,0.00002491346],"domain_scores_gemma":[0.9994252,0.0003410799,0.00003551614,0.00002871215,0.0001421711,0.0000274013],"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":[0.0001215385,0.00008074845,0.0003157995,0.00003294571,0.0000207362,0.00002951869,0.00001921232,0.9220112,0.002503696,0.003135948,0.0007731813,0.0709555],"study_design_scores_gemma":[0.000003547754,0.00001379554,0.00002323352,0.000001054115,0.000002218221,0.000002641405,8.979457e-7,0.9992932,0.0002458137,0.0003664971,0.00004583822,0.000001228037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1261267,0.0007864236,0.8664801,0.0004108603,0.000196583,0.00006027773,0.00004530668,0.0004809297,0.005412797],"genre_scores_gemma":[0.8943765,0.0002195051,0.1012916,0.0001529669,0.00007455895,0.00006589411,0.0000452034,0.00004875558,0.003724985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004044407,"threshold_uncertainty_score":0.008041739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01961511457914447,"score_gpt":0.2435076267389591,"score_spread":0.2238925121598146,"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."}}