{"id":"W2765288170","doi":"10.1142/s0218213017600168","title":"Multi-Objective Optimization in Multi-Attribute and Multi-Unit Combinatorial Reverse Auctions","year":2017,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Mathematical optimization; Elitism; Heuristic; Combinatorial auction; Quality (philosophy); Scalability; Convergence (economics); Genetic algorithm; Common value auction; Diversity (politics); Machine learning; Artificial intelligence; Mathematics","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":[0.005872475,0.001395106,0.002645866,0.001526769,0.0005656368,0.002292686,0.002532287,0.001941276,0.001858448],"category_scores_gemma":[0.007437977,0.0009747499,0.001731413,0.002340905,0.001381303,0.001965419,0.0014103,0.002071268,0.0003065428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375848,"about_ca_system_score_gemma":0.001219859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002117858,"about_ca_topic_score_gemma":0.001572788,"domain_scores_codex":[0.9954632,0.003041047,0.0001582879,0.0004066031,0.000671184,0.0002596507],"domain_scores_gemma":[0.9958832,0.003047902,0.0004243138,0.0002171869,0.0002791335,0.0001482752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000412312,0.00007902846,0.0003082756,0.0001219545,0.00008948917,0.0001209663,0.00003660184,0.9714025,0.0004401541,0.01424634,0.0002572663,0.01285622],"study_design_scores_gemma":[0.00001898082,0.00004946382,0.00008183057,0.00001248732,0.00001713212,0.00005441981,0.00001781037,0.9892564,0.0002155969,0.009910637,0.0003562297,0.000009062489],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02877315,0.0007176064,0.9674407,0.0001649367,0.00005209681,0.000118475,0.00004966028,0.00008019315,0.002603121],"genre_scores_gemma":[0.5575814,0.000590298,0.4375713,0.0001895939,0.00007504528,0.0003383161,0.0001082159,0.00008869125,0.003457098],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005872475,"threshold_uncertainty_score":0.031057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3136507355222871,"score_gpt":0.4696876422128266,"score_spread":0.1560369066905395,"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."}}