{"id":"W2770312206","doi":"10.1080/00207543.2017.1401249","title":"Scheduling twin robots in a palletising problem","year":2017,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"University of Bath; Canadian Natural Resources Limited","keywords":"Iterated local search; Mathematical optimization; Robot; Metaheuristic; Job shop scheduling; Integer programming; Computer science; Scheduling (production processes); Linear programming; Iterated function; Mathematics; Artificial intelligence; Routing (electronic design automation)","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":[0.001625927,0.001214293,0.002042793,0.0007165826,0.0009297446,0.001909085,0.001699796,0.002027572,0.005087316],"category_scores_gemma":[0.003043397,0.001037129,0.001174428,0.00124736,0.00121585,0.002660754,0.001766403,0.001878769,0.0005838124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000900378,"about_ca_system_score_gemma":0.00125022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244337,"about_ca_topic_score_gemma":0.001378023,"domain_scores_codex":[0.998713,0.0005000689,0.00007333427,0.0003244311,0.0002118649,0.0001771805],"domain_scores_gemma":[0.9988093,0.000715938,0.0001494322,0.00008594914,0.00008114053,0.0001582352],"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":[0.0003435805,0.0001768417,0.000543502,0.0002811406,0.00007575571,0.0005361303,0.0001849909,0.9375715,0.003577675,0.02995692,0.0009454499,0.02580644],"study_design_scores_gemma":[0.00007681033,0.000303231,0.0002597806,0.00001757783,0.00004109597,0.0002461682,0.000132047,0.9652497,0.001892868,0.02819276,0.0035634,0.00002456678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1066297,0.0005932253,0.8826831,0.0003716103,0.0001303131,0.0002306798,0.0001280919,0.000307533,0.008925811],"genre_scores_gemma":[0.642393,0.0006508279,0.3453269,0.0001420781,0.00008697363,0.0002923461,0.0003225561,0.0001502894,0.01063502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005087316,"threshold_uncertainty_score":0.0170188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09154275540480063,"score_gpt":0.403095946266704,"score_spread":0.3115531908619034,"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."}}