{"id":"W2053855832","doi":"10.1007/s10479-006-0148-y","title":"Coordinating decentralized local schedulers in complex supply chain manufacturing","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Scheduling (production processes); Computer science; Supply chain; Theory of computation; Distributed computing; Schedule; Production schedule; Dynamic priority scheduling; Job shop scheduling; Production planning; Industrial engineering; Production (economics); Operations management; Engineering; Business; Algorithm","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":[0.0007917135,0.00009773719,0.0001577967,0.0004384101,0.0001396925,0.00008196556,0.0001722998,0.00006868304,0.0002645736],"category_scores_gemma":[0.00008428449,0.0001046237,0.00003802554,0.0005063272,0.0001073326,0.0001617834,0.00003346199,0.0002761304,0.00002721499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000431861,"about_ca_system_score_gemma":0.00004113484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007329223,"about_ca_topic_score_gemma":0.0003697966,"domain_scores_codex":[0.9986365,0.0001118317,0.0003415242,0.0001516421,0.0003434132,0.0004150397],"domain_scores_gemma":[0.9994205,0.00009616663,0.000008928759,0.0001707654,0.000238873,0.00006476313],"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":[0.000005505913,0.00004441591,0.0003573353,0.00002392986,0.000008723761,0.000004223722,0.0001195461,0.992227,0.001103039,0.001038635,0.00105494,0.004012667],"study_design_scores_gemma":[0.0003848386,0.00001883074,0.004884994,0.00003692987,8.728551e-7,0.000001760332,0.0004075337,0.941377,0.0522158,0.00008053275,0.0004840332,0.0001067991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9307402,0.0005932964,0.06222803,0.002118305,0.00007542082,0.0003831424,0.00002516603,0.0001374128,0.003699029],"genre_scores_gemma":[0.9727727,0.0001004716,0.02675944,0.00002463856,0.00005339305,0.00003150099,0.00008695223,0.00002277188,0.0001481731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05111276,"threshold_uncertainty_score":0.4266433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103442901711207,"score_gpt":0.3753957638955624,"score_spread":0.2719528621843553,"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."}}