{"id":"W3125454972","doi":"10.14488/bjopm.2021.007","title":"A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability","year":2021,"lang":"en","type":"article","venue":"Brazilian Journal of Operations & Production Management","topic":"BIM and Construction Integration","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Scheduling (production processes); Schedule; Fair-share scheduling; Dynamic priority scheduling; Genetic algorithm scheduling; Mathematical optimization; Job shop scheduling; Heuristic; Rate-monotonic scheduling; Operations research; Industrial engineering; Engineering; 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":[0.001138739,0.001058339,0.00117141,0.0009557984,0.0007217151,0.0009662212,0.001290609,0.00141729,0.003173844],"category_scores_gemma":[0.001395419,0.0006317089,0.001013223,0.0008713786,0.0004044882,0.0007396565,0.0008229751,0.001108441,0.0003820933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008709701,"about_ca_system_score_gemma":0.002515415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008485259,"about_ca_topic_score_gemma":0.006732182,"domain_scores_codex":[0.9995611,0.00013784,0.00002590433,0.00009650821,0.0001024389,0.00007615158],"domain_scores_gemma":[0.9994629,0.0002754728,0.00008164023,0.00001892844,0.000123357,0.00003781519],"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":[0.00005261887,0.00004146144,0.0003915172,0.00009804106,0.00003954445,0.00007217976,0.00005502112,0.9571809,0.001127109,0.002389654,0.0007638602,0.03778809],"study_design_scores_gemma":[0.00001893858,0.00003225734,0.00007379209,0.00001015205,0.000008096275,0.00001564748,0.00001375835,0.9984585,0.0002211445,0.0006876811,0.0004558535,0.000004177573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02060931,0.0003569241,0.9743825,0.0001825452,0.00006306691,0.0001545534,0.00007636688,0.0003819943,0.003792715],"genre_scores_gemma":[0.3604282,0.0003392944,0.6343427,0.0001167739,0.00005138042,0.0005898676,0.0002605985,0.0001026035,0.003768608],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008485259,"threshold_uncertainty_score":0.01687175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02728986193083059,"score_gpt":0.2833625452469981,"score_spread":0.2560726833161674,"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."}}