{"id":"W2561895128","doi":"10.1504/ijads.2016.081393","title":"A new heuristic memory-based simulated annealing approach applied to mine production scheduling problem","year":2016,"lang":"en","type":"article","venue":"International Journal of Applied Decision Sciences","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Simulated annealing; Mathematical optimization; Computer science; Scheduling (production processes); Heuristic; Job shop scheduling; Algorithm; Mathematics; Schedule","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001054137,0.0001436113,0.0002162213,0.0005355126,0.00006356602,0.0001407596,0.0007266533,0.00005945941,0.00005277019],"category_scores_gemma":[0.0001300601,0.00009924168,0.00006423829,0.0003008466,0.00004512967,0.0001861619,0.00005637792,0.0001077303,0.00002683568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376085,"about_ca_system_score_gemma":0.0001054887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003067621,"about_ca_topic_score_gemma":0.000001314197,"domain_scores_codex":[0.998298,0.000004424068,0.0006496783,0.0002493952,0.000605808,0.0001927166],"domain_scores_gemma":[0.9991391,0.0001835688,0.0002170612,0.0001321661,0.0001751896,0.0001529562],"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":[0.0001487626,0.00001660532,0.00002395312,0.00000425966,0.00002155594,0.0000021589,0.0001126775,0.8637924,0.02372248,0.0007732272,0.0017602,0.1096218],"study_design_scores_gemma":[0.005324698,0.0005137742,0.0006166284,0.00158266,0.00007325478,0.0002133393,0.0007490145,0.5754861,0.3223598,0.07298414,0.01848548,0.001611129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3383279,0.00002705109,0.6577445,0.0003465998,0.0005851343,0.0001405462,0.000002115012,0.00007073145,0.002755451],"genre_scores_gemma":[0.6231006,0.00001201979,0.3765256,0.00005611899,0.0002814721,0.000002853961,5.412528e-7,0.000011167,0.000009529457],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2986373,"threshold_uncertainty_score":0.4046958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02678745024188873,"score_gpt":0.2798924677841571,"score_spread":0.2531050175422684,"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."}}