{"id":"W2046858085","doi":"10.1007/s12293-014-0141-y","title":"Incorporating domain-specific heuristics in a particle swarm optimization approach to the quadratic assignment problem","year":2014,"lang":"en","type":"article","venue":"Memetic Computing","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brandon University","funders":"","keywords":"Heuristics; Particle swarm optimization; Complex system; Domain (mathematical analysis); Quadratic equation; Mathematical optimization; Computer science; Multi-swarm optimization; Metaheuristic; Quadratic assignment problem; Algorithm; Mathematics; Optimization problem; 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":[0.001379509,0.0005764216,0.0007862085,0.0007165915,0.0004983511,0.001011846,0.001227327,0.00132203,0.001661283],"category_scores_gemma":[0.004338906,0.0004987671,0.0005308783,0.0009036254,0.0006992096,0.001027338,0.0009327492,0.001089265,0.0002842135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005754917,"about_ca_system_score_gemma":0.0009813131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003681794,"about_ca_topic_score_gemma":0.005049207,"domain_scores_codex":[0.9995804,0.0002280261,0.00001771939,0.00003950121,0.0001023944,0.00003186209],"domain_scores_gemma":[0.9989489,0.0006996185,0.0000720387,0.00008233067,0.0001634204,0.00003380275],"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":[0.00001836281,0.00003240235,0.0001232616,0.00002656955,0.00001607834,0.00001896133,0.00002240513,0.9712549,0.0003893234,0.009385674,0.0004929791,0.01821908],"study_design_scores_gemma":[0.000007456554,0.00001186946,0.00002202238,0.000002968421,0.000003724739,0.000005001031,0.000003890181,0.9973099,0.00009672095,0.002253846,0.0002802885,0.000002230733],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01061257,0.0001480556,0.9840883,0.0001974955,0.00007862927,0.00004498099,0.00001834388,0.0001005697,0.004711094],"genre_scores_gemma":[0.4300947,0.0003223048,0.5659027,0.0002266112,0.0001262118,0.0002003752,0.00007871853,0.00009332825,0.002955121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003681794,"threshold_uncertainty_score":0.007320762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.025472997722235,"score_gpt":0.2556864356005865,"score_spread":0.2302134378783515,"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."}}