{"id":"https://openalex.org/W2169641440","doi":"https://doi.org/10.1109/tevc.2009.2033583","title":"A Hybrid Evolutionary Approach to the Nurse Rostering Problem","display_name":"A Hybrid Evolutionary Approach to the Nurse Rostering Problem","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2169641440","doi":"https://doi.org/10.1109/tevc.2009.2033583","mag":"2169641440"},"language":"en","primary_location":{"id":"doi:10.1109/tevc.2009.2033583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2009.2033583","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://eprints.nottingham.ac.uk/47488/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046750599","display_name":"Ruibin Bai","orcid":"https://orcid.org/0000-0003-1722-568X"},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruibin Bai","raw_affiliation_strings":["Division of Computer Science, University of Nottingham, Ningbo, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"Division of Computer Science, University of Nottingham, Ningbo, Ningbo, China","institution_ids":["https://openalex.org/I13591777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004567468","display_name":"Edmund Burke","orcid":"https://orcid.org/0000-0003-0712-4762"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Edmund K. Burke","raw_affiliation_strings":["School of Computer Science, University of Nottingham, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074319022","display_name":"Graham Kendall","orcid":"https://orcid.org/0000-0003-2006-5103"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Graham Kendall","raw_affiliation_strings":["School of Computer Science, University of Nottingham, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078385256","display_name":"Jingpeng Li","orcid":"https://orcid.org/0000-0002-6758-0084"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jingpeng Li","raw_affiliation_strings":["School of Computer Science, University of Nottingham, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110492315","display_name":"Barry McCollum","orcid":null},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Barry McCollum","raw_affiliation_strings":["Department of Computer Science, School of Electronics, Electrical Engineering and Computer Science, Queen''s University Belfast, Belfast, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, School of Electronics, Electrical Engineering and Computer Science, Queen''s University Belfast, Belfast, UK","institution_ids":["https://openalex.org/I126231945"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046750599"],"corresponding_institution_ids":["https://openalex.org/I13591777"],"apc_list":null,"apc_paid":null,"fwci":9.3059,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.97927768,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"14","issue":"4","first_page":"580","last_page":"590"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12401","display_name":"Scheduling and Timetabling Solutions","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12401","display_name":"Scheduling and Timetabling Solutions","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9635999798774719,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6429858803749084},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6245923042297363},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.560977578163147},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.505455493927002},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4857671558856964},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4823538661003113},{"id":"https://openalex.org/keywords/local-search","display_name":"Local search (optimization)","score":0.48005542159080505},{"id":"https://openalex.org/keywords/penalty-method","display_name":"Penalty method","score":0.475458562374115},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4733450710773468},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44632643461227417},{"id":"https://openalex.org/keywords/hybrid-algorithm","display_name":"Hybrid algorithm (constraint satisfaction)","score":0.43587034940719604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31884652376174927},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.288871705532074},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23024296760559082},{"id":"https://openalex.org/keywords/constraint-satisfaction","display_name":"Constraint satisfaction","score":0.18572601675987244},{"id":"https://openalex.org/keywords/constraint-logic-programming","display_name":"Constraint logic programming","score":0.12139692902565002},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.10793900489807129}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6429858803749084},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6245923042297363},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.560977578163147},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.505455493927002},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4857671558856964},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4823538661003113},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.48005542159080505},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.475458562374115},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4733450710773468},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44632643461227417},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.43587034940719604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31884652376174927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.288871705532074},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23024296760559082},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.18572601675987244},{"id":"https://openalex.org/C176783269","wikidata":"https://www.wikidata.org/wiki/Q5164378","display_name":"Constraint logic programming","level":4,"score":0.12139692902565002},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.10793900489807129},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":8,"locations":[{"id":"doi:10.1109/tevc.2009.2033583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2009.2033583","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.153.2045","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.2045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.qub.ac.uk/~B.McCollum/publications/HEA_Bmc_NR.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.158.9642","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.9642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.nott.ac.uk/~ekb/Publications/IEEE_TEVC2010.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.301.2050","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.2050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.nott.ac.uk/~rzb/publications/nurse-tevc.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.330.4937","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.4937","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.nott.ac.uk/~jpl/papers/IEEE_TEVC2010.pdf","raw_type":"text"},{"id":"pmh:oai:eprints.nottingham.ac.uk:47488","is_oa":true,"landing_page_url":"http://eprints.nottingham.ac.uk/47488/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402013","display_name":"Nottingham ePrints (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:nottingham-repository.worktribe.com:706516","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/output/706516","pdf_url":null,"source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"acceptedVersion"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/cd182da0-64b7-435c-a170-6986af046264","is_oa":false,"landing_page_url":"https://pure.qub.ac.uk/en/publications/cd182da0-64b7-435c-a170-6986af046264","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Burke, E K, Kendall, G, Jinpeng, L & McCollum, B 2010, 'A Hybrid Evolutionary Approach to the Nurse Rostering Problem', IEEE Transactions on Evolutionary Computation, vol. 14, no. 4, pp. 580-590. https://doi.org/10.1109/TEVC.2009.2033583","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:eprints.nottingham.ac.uk:47488","is_oa":true,"landing_page_url":"http://eprints.nottingham.ac.uk/47488/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402013","display_name":"Nottingham ePrints (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W44844361","https://openalex.org/W107452617","https://openalex.org/W147602573","https://openalex.org/W167027853","https://openalex.org/W1497256448","https://openalex.org/W1546381774","https://openalex.org/W1567102157","https://openalex.org/W1572910922","https://openalex.org/W1586409345","https://openalex.org/W1639032689","https://openalex.org/W1651333704","https://openalex.org/W1659842140","https://openalex.org/W1668207500","https://openalex.org/W1680972677","https://openalex.org/W1963988630","https://openalex.org/W1979126188","https://openalex.org/W1980913658","https://openalex.org/W1981097545","https://openalex.org/W2003143905","https://openalex.org/W2004217556","https://openalex.org/W2008026888","https://openalex.org/W2009281987","https://openalex.org/W2013067314","https://openalex.org/W2016721869","https://openalex.org/W2021010829","https://openalex.org/W2023795630","https://openalex.org/W2056956492","https://openalex.org/W2059859274","https://openalex.org/W2074059988","https://openalex.org/W2080747453","https://openalex.org/W2085033701","https://openalex.org/W2087525580","https://openalex.org/W2109694902","https://openalex.org/W2133671908","https://openalex.org/W2145479420","https://openalex.org/W2151339633","https://openalex.org/W2152150600","https://openalex.org/W2155207871","https://openalex.org/W2161029074","https://openalex.org/W2170186790","https://openalex.org/W2170338867","https://openalex.org/W2544340949","https://openalex.org/W2904250082","https://openalex.org/W3023540311","https://openalex.org/W3103464856","https://openalex.org/W3104933531","https://openalex.org/W3125132395","https://openalex.org/W6601791335","https://openalex.org/W6604361150","https://openalex.org/W6636937994","https://openalex.org/W6637533551"],"related_works":["https://openalex.org/W2111761631","https://openalex.org/W2107782179","https://openalex.org/W3203254889","https://openalex.org/W4224307044","https://openalex.org/W2097905284","https://openalex.org/W2378678635","https://openalex.org/W2111203151","https://openalex.org/W2005666100","https://openalex.org/W2359458683","https://openalex.org/W2391650495"],"abstract_inverted_index":{"Nurse":[0],"rostering":[1,71],"is":[2,79],"an":[3,37],"important":[4],"search":[5,118],"problem":[6],"with":[7,91,107,137],"many":[8],"constraints.":[9],"In":[10,32],"the":[11,75,94,99,102,127,134,141,149,152,156],"literature,":[12],"a":[13,40,59,108,116],"number":[14],"of":[15,39,61,101],"approaches":[16],"have":[17,155],"been":[18],"investigated":[19],"including":[20],"penalty":[21],"function":[22],"methods":[23,150],"to":[24,51,87,93],"tackle":[25],"these":[26],"constraints":[27],"within":[28,115],"genetic":[29,120,135],"algorithm":[30,121,129,136,146],"frameworks.":[31],"this":[33],"paper,":[34],"we":[35,104],"investigate":[36],"extension":[38],"previously":[41,157],"proposed":[42,110],"stochastic":[43,76,138],"ranking":[44,77,139],"method,":[45],"which":[46,154],"has":[47],"demonstrated":[48],"superior":[49],"performance":[50,100],"other":[52],"constraint":[53],"handling":[54],"techniques":[55],"when":[56],"tested":[57],"against":[58],"set":[60],"constrained":[62],"optimization":[63],"benchmark":[64],"problems.":[65],"An":[66],"initial":[67],"experiment":[68],"on":[69],"nurse":[70],"problems":[72],"demonstrates":[73],"that":[74,126],"method":[78],"better":[80,131],"at":[81],"finding":[82],"feasible":[83],"solutions,":[84],"but":[85],"fails":[86],"obtain":[88],"good":[89],"results":[90,124],"regard":[92],"objective":[95],"function.":[96],"To":[97],"improve":[98],"algorithm,":[103],"hybridize":[105],"it":[106],"recently":[109],"simulated":[111],"annealing":[112],"hyper-heuristic":[113],"(SAHH)":[114],"local":[117],"and":[119,140],"framework.":[122],"Computational":[123],"show":[125],"hybrid":[128,145],"performs":[130],"than":[132],"both":[133],"SAHH":[142],"alone.":[143],"The":[144],"also":[147],"outperforms":[148],"in":[151],"literature":[153],"best":[158],"known":[159],"results.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":12},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":5}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
