{"id":"W2621009047","doi":"","title":"Variable Neighborhood Search for Minimum Cost Berth Allocation","year":2003,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Variable neighborhood search; Mathematical optimization; Tardiness; Minification; Heuristic; Variable (mathematics); Computer science; Genetic algorithm; Memetic algorithm; Local search (optimization); Function (biology); Retard; Mathematics; Metaheuristic; Job shop scheduling","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":[],"consensus_categories":[],"category_scores_codex":[0.001189239,0.0001309902,0.0001922105,0.0001708158,0.0001036064,0.00007626665,0.0001808975,0.000135401,0.0002715522],"category_scores_gemma":[0.0002898675,0.0001479044,0.00004284054,0.000136745,0.00007517183,0.0000894101,0.00003197605,0.0003200506,0.00001141809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106405,"about_ca_system_score_gemma":0.0001626502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000020801,"about_ca_topic_score_gemma":0.00005534428,"domain_scores_codex":[0.9985948,0.00005615974,0.0003041327,0.0002760734,0.0001166,0.0006522025],"domain_scores_gemma":[0.9989473,0.0004440731,0.00001761873,0.0003589702,0.00008897107,0.0001430811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000843528,0.0003207965,0.01122798,0.0005467812,0.00016373,0.00001931613,0.0004177039,0.3047888,0.001327122,0.2319366,0.002151637,0.4470152],"study_design_scores_gemma":[0.001528598,0.0001602185,0.001348845,0.00005347793,0.00001067278,0.00001544801,0.0005196251,0.492741,0.002532282,0.005202705,0.4953226,0.0005645692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01585004,0.0001440549,0.005745314,0.0001112776,0.0004669669,0.001354609,0.00007033853,0.0001127681,0.9761446],"genre_scores_gemma":[0.9896945,0.001113478,0.005341979,0.00004917829,0.0001213122,0.0002660055,0.00006426917,0.00006914792,0.003280172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9738444,"threshold_uncertainty_score":0.6031367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02626859360425234,"score_gpt":0.2750029009678145,"score_spread":0.2487343073635622,"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."}}