{"id":"W2899710160","doi":"10.1007/s13369-018-3617-0","title":"Discrete Sine-Cosine Algorithm (DSCA) with Local Search for Solving Traveling Salesman Problem","year":2018,"lang":"en","type":"article","venue":"Arabian Journal for Science and Engineering","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Travelling salesman problem; Trigonometric functions; Mathematical optimization; Algorithm; Crossover; Computer science; Heuristic; Optimization problem; Mathematics; Artificial intelligence","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":[0.0007469709,0.0006184281,0.00115751,0.0007758618,0.0005855745,0.0006300173,0.001289029,0.0009927517,0.003133493],"category_scores_gemma":[0.001858976,0.0003078393,0.0006763412,0.001510992,0.0004990646,0.0008230002,0.0007283398,0.001183468,0.0004134111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005685279,"about_ca_system_score_gemma":0.001693893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004961364,"about_ca_topic_score_gemma":0.004289644,"domain_scores_codex":[0.9996039,0.0001267252,0.00002488187,0.00006487335,0.0001420477,0.00003757992],"domain_scores_gemma":[0.9995611,0.0002243068,0.00003169908,0.00003244004,0.0001210848,0.00002931474],"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":[0.0001851972,0.0002592155,0.0007603249,0.0002673868,0.00008265556,0.00006565393,0.000109861,0.7411332,0.004246966,0.03094451,0.004415544,0.2175295],"study_design_scores_gemma":[0.00002570072,0.00006942742,0.00006434719,0.000006297145,0.000008183253,0.00002192316,0.00001130682,0.9961985,0.0004583161,0.002120865,0.001010971,0.000004185317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03094155,0.001231414,0.9594462,0.0002408286,0.0002500456,0.0001142325,0.00004443917,0.0003148069,0.007416422],"genre_scores_gemma":[0.401633,0.0007278793,0.5911947,0.0001688956,0.0001314202,0.000314155,0.0001843274,0.0001065579,0.005539145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004961364,"threshold_uncertainty_score":0.01048261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01859448136858305,"score_gpt":0.2773544058793667,"score_spread":0.2587599245107837,"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."}}