{"id":"W1999841317","doi":"10.1016/j.cie.2004.02.002","title":"Coordinating production planning in cellular manufacturing environment using Tabu search","year":2004,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tabu search; Cellular manufacturing; Production planning; Production (economics); Cell formation; Mathematical optimization; Quadratic equation; Material requirements planning; Computer science; Engineering; Industrial engineering; Operations research; Manufacturing engineering; Mathematics; Economics","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":[0.001123169,0.0008178693,0.001332925,0.001223751,0.001053697,0.001634124,0.001180879,0.001195494,0.003769347],"category_scores_gemma":[0.002299817,0.0007669521,0.0006013945,0.002611543,0.0005375082,0.001122007,0.0008750841,0.0006087445,0.0004325387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003141,"about_ca_system_score_gemma":0.001938167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01261389,"about_ca_topic_score_gemma":0.01199743,"domain_scores_codex":[0.9994501,0.0002379717,0.00002264852,0.00008619397,0.00007649657,0.0001265591],"domain_scores_gemma":[0.9990395,0.000533517,0.0001001034,0.0000778181,0.0001586599,0.00009041712],"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":[0.0001648014,0.00007298698,0.0005776263,0.00004216531,0.00003607313,0.00006471063,0.00004282781,0.9629544,0.001070821,0.001644505,0.001008799,0.03232029],"study_design_scores_gemma":[0.00002241069,0.0000537883,0.0001328873,0.000002918734,0.00001349468,0.00001035263,0.00003201931,0.9974183,0.0005142077,0.00143668,0.0003589089,0.000004074616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2138435,0.0008302635,0.772806,0.0003591885,0.0001187484,0.0002153844,0.0002806609,0.001392863,0.01015333],"genre_scores_gemma":[0.8057988,0.0002260782,0.1911774,0.00008107412,0.00002572882,0.0001683065,0.0002854239,0.0001341979,0.002102908],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01261389,"threshold_uncertainty_score":0.02508092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03484674269641679,"score_gpt":0.2175207130587768,"score_spread":0.18267397036236,"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."}}