{"id":"W2039309022","doi":"10.1109/tnet.2014.2362356","title":"A Hybrid Iterated Local Search Algorithm for the Global Planning Problem of Survivable 4G Wireless Networks","year":2014,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Iterated local search; Computer science; Mathematical optimization; Integer programming; Heuristic; Algorithm; Local search (optimization); Hybrid algorithm (constraint satisfaction); Wireless network; Iterated function; Wireless; Mathematics; Local consistency; Constraint satisfaction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001424943,0.000375055,0.0004647846,0.00009019452,0.0007627706,0.000293831,0.001891085,0.0001741343,0.000008163787],"category_scores_gemma":[0.000004089428,0.0003169327,0.0002481481,0.001074581,0.0001787795,0.0003207976,0.00004616719,0.0006266606,0.000004950632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001722022,"about_ca_system_score_gemma":0.0001051493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001214317,"about_ca_topic_score_gemma":0.00004897997,"domain_scores_codex":[0.9967483,0.0003257408,0.0006292834,0.0007500111,0.0005351417,0.001011553],"domain_scores_gemma":[0.9964653,0.001639044,0.0002118575,0.001261919,0.000242472,0.0001794263],"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":[0.00002397336,0.00005081236,0.00005519313,0.00001191811,0.00006344917,0.000003000604,0.00005891377,0.5352808,0.000003658074,0.0004385862,0.0001280798,0.4638816],"study_design_scores_gemma":[0.0007384668,0.0002586291,0.00005962741,0.0002843488,0.00003908789,0.00003962369,0.00002617052,0.9924971,0.0003408137,0.001258538,0.004136109,0.0003214525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000734677,0.0003733205,0.995395,0.0002122724,0.001847491,0.0009104616,0.00001336649,0.0002736428,0.0002397873],"genre_scores_gemma":[0.9296679,0.00006853222,0.06876923,0.0002296054,0.0008892303,0.0002419345,0.00000952627,0.00004639399,0.00007758751],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9289333,"threshold_uncertainty_score":0.9999283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212066330877365,"score_gpt":0.2632879101337656,"score_spread":0.241167246824992,"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."}}