{"id":"W3127712221","doi":"10.1155/2021/6627081","title":"Two‐Agent Single Machine Order Acceptance Scheduling Problem to Maximize Net Revenue","year":2021,"lang":"en","type":"article","venue":"Complexity","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Computer science; Particle swarm optimization; Metaheuristic; Benchmark (surveying); Job shop scheduling; Scheduling (production processes); Heuristic; Integer programming; Mathematics; Schedule","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":[0.00166822,0.001443409,0.001991766,0.0007962646,0.0007112005,0.002019784,0.001633308,0.001394782,0.003143369],"category_scores_gemma":[0.002197549,0.0005062362,0.001013247,0.001523857,0.0006098909,0.001175024,0.0009442591,0.001426688,0.0004687059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00105023,"about_ca_system_score_gemma":0.002167756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003039205,"about_ca_topic_score_gemma":0.001976529,"domain_scores_codex":[0.9984899,0.0006466206,0.0000715624,0.0001971826,0.0003650979,0.0002297147],"domain_scores_gemma":[0.9983683,0.0008824136,0.0002438432,0.00007860165,0.0002734513,0.0001532871],"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":[0.0002206115,0.0002315528,0.0006429008,0.0003104304,0.00008928552,0.0002987442,0.00008966687,0.9495083,0.003186939,0.02056544,0.001935747,0.02292043],"study_design_scores_gemma":[0.00003021468,0.00007243792,0.0001255397,0.000006011798,0.00001118875,0.00004634351,0.0000267787,0.9942972,0.0006421118,0.003736805,0.0009989392,0.000006484707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08480357,0.0007035912,0.8980205,0.0008061745,0.0001953023,0.000449418,0.0002383279,0.0002970316,0.01448609],"genre_scores_gemma":[0.8145197,0.0006277718,0.1741863,0.0001214743,0.0001649469,0.0005854677,0.0003601737,0.00009408596,0.009340058],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003143369,"threshold_uncertainty_score":0.01051563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04472565511332127,"score_gpt":0.2655855424775029,"score_spread":0.2208598873641817,"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."}}