{"id":"W2887130754","doi":"10.11159/icmie18.102","title":"Hybridizing Ant Colony Optimization by Beam Search for the Assembly Line Balancing Problem","year":2018,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hong Kong Polytechnic University; National Natural Science Foundation of China","keywords":"Ant colony optimization algorithms; Assembly line; Computer science; Metaheuristic; Mathematical optimization; Line (geometry); Ant colony; ANT; Artificial intelligence; Engineering; Mathematics; Mechanical engineering; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001467244,0.00112877,0.001082015,0.001273014,0.0004210556,0.0007889794,0.001121662,0.00112839,0.001867777],"category_scores_gemma":[0.002400816,0.0005497875,0.0009411917,0.001215067,0.0005040543,0.000871391,0.0008155284,0.0009369928,0.0003423129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005274623,"about_ca_system_score_gemma":0.001179617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008502326,"about_ca_topic_score_gemma":0.006442322,"domain_scores_codex":[0.9992931,0.0003190679,0.00002850397,0.00008877831,0.0001690217,0.0001015293],"domain_scores_gemma":[0.9988248,0.0007414562,0.0001186819,0.00006084011,0.0001906931,0.00006345465],"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":[0.00008472148,0.0001000957,0.0009793045,0.00006592079,0.0000628744,0.00005059742,0.00003558992,0.9665723,0.001694713,0.002201019,0.001023251,0.02712958],"study_design_scores_gemma":[0.0000255914,0.00003463236,0.000122675,0.000004920751,0.000008496468,0.000007621742,0.000008103335,0.9987699,0.0002106829,0.0005612526,0.0002428954,0.000003227092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.17762,0.00160913,0.809136,0.0006686655,0.0001891777,0.0002330721,0.0001612421,0.0009553905,0.009427353],"genre_scores_gemma":[0.6872996,0.0005622869,0.3080969,0.0005226553,0.00007022515,0.0004158947,0.0003373232,0.0001647575,0.002530433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008502326,"threshold_uncertainty_score":0.01690567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006016475930006124,"score_gpt":0.2088847769223841,"score_spread":0.2028683009923779,"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."}}