{"id":"W2103762423","doi":"10.1109/cec.2011.5949919","title":"A Machine Operation Lists based Memetic Algorithm for Job Shop Scheduling","year":2011,"lang":"en","type":"article","venue":"","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Crossover; Job shop scheduling; Flow shop scheduling; Memetic algorithm; Computer science; Mathematical optimization; Benchmark (surveying); Job shop; Scheduling (production processes); Schedule; Genetic algorithm; Algorithm; Local search (optimization); Mathematics; Artificial intelligence","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":[0.0008304461,0.0006252195,0.0007636892,0.000897649,0.0006049566,0.0006161988,0.001350449,0.001132364,0.001703085],"category_scores_gemma":[0.001329143,0.0003087622,0.0006864095,0.0008612178,0.0004899269,0.0007769709,0.0005043126,0.000709784,0.0003318508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006036631,"about_ca_system_score_gemma":0.0007371145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008534786,"about_ca_topic_score_gemma":0.0008786148,"domain_scores_codex":[0.9995822,0.0001659564,0.00002234706,0.00005170396,0.0001441155,0.00003365256],"domain_scores_gemma":[0.9996532,0.0001806709,0.00004095586,0.0000337619,0.00007591974,0.00001544216],"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":[0.0001414253,0.0001237795,0.000571664,0.0002508319,0.0001697797,0.0001583149,0.0001078845,0.7795501,0.009022427,0.03272324,0.004072121,0.1731084],"study_design_scores_gemma":[0.00003109693,0.00006037587,0.00009415898,0.000007653973,0.00001440163,0.00006850513,0.000008073851,0.9912203,0.001652829,0.003566429,0.003264762,0.00001149052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01360834,0.0006640042,0.9805177,0.000242202,0.0001872013,0.0001001597,0.00004376994,0.0004009332,0.004235723],"genre_scores_gemma":[0.3720666,0.0006366892,0.6187254,0.0002982435,0.0001686066,0.0006519377,0.000139704,0.00008871101,0.007224084],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001703085,"threshold_uncertainty_score":0.00569737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02572089430947704,"score_gpt":0.2351059558453641,"score_spread":0.2093850615358871,"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."}}