{"id":"https://openalex.org/W4406461858","doi":"https://doi.org/10.1109/bigdata62323.2024.10825745","title":"An Efficient Modeling Approach for Nurse Rostering Problem: Use Case","display_name":"An Efficient Modeling Approach for Nurse Rostering Problem: Use Case","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461858","doi":"https://doi.org/10.1109/bigdata62323.2024.10825745"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018007154","display_name":"Walid Abdelaidoum","orcid":null},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Walid Abdelaidoum","raw_affiliation_strings":["University of Paris 8,LIASD Laboratory,France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD Laboratory,France","institution_ids":["https://openalex.org/I48825208","https://openalex.org/I204730241"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005273692","display_name":"Mohamed A. Madani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohamed A. Madani","raw_affiliation_strings":["SWAPPY,Paris,France"],"affiliations":[{"raw_affiliation_string":"SWAPPY,Paris,France","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074810075","display_name":"Larbi Boubchir","orcid":"https://orcid.org/0000-0002-5668-6801"},"institutions":[{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]},{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Larbi Boubchir","raw_affiliation_strings":["University of Paris 8,LIASD Laboratory,France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD Laboratory,France","institution_ids":["https://openalex.org/I48825208","https://openalex.org/I204730241"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044161230","display_name":"Boubaker Da\u00e2chi","orcid":"https://orcid.org/0000-0002-8910-517X"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]},{"id":"https://openalex.org/I48825208","display_name":"Universit\u00e9 Paris 8","ror":"https://ror.org/04wez5e68","country_code":"FR","type":"education","lineage":["https://openalex.org/I48825208"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Boubaker Daachi","raw_affiliation_strings":["University of Paris 8,LIASD Laboratory,France"],"affiliations":[{"raw_affiliation_string":"University of Paris 8,LIASD Laboratory,France","institution_ids":["https://openalex.org/I48825208","https://openalex.org/I204730241"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5018007154"],"corresponding_institution_ids":["https://openalex.org/I204730241","https://openalex.org/I48825208"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32115913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4548","last_page":"4553"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12401","display_name":"Scheduling and Timetabling Solutions","score":0.9998000264167786,"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":0.9998000264167786,"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/T12782","display_name":"Assembly Line Balancing Optimization","score":0.9126999974250793,"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/T11773","display_name":"Healthcare Operations and Scheduling Optimization","score":0.9124000072479248,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6518625617027283},{"id":"https://openalex.org/keywords/nursing","display_name":"Nursing","score":0.3500387668609619},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17466062307357788}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518625617027283},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.3500387668609619},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17466062307357788}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1995251200","https://openalex.org/W2003507865","https://openalex.org/W2003790321","https://openalex.org/W2016721869","https://openalex.org/W2021010829","https://openalex.org/W2114494151","https://openalex.org/W2155207871","https://openalex.org/W2523385593","https://openalex.org/W2582489078","https://openalex.org/W2789793843","https://openalex.org/W4285292539","https://openalex.org/W4385301057","https://openalex.org/W4391052907","https://openalex.org/W4392385107","https://openalex.org/W4392458156","https://openalex.org/W4392736302","https://openalex.org/W4396228585","https://openalex.org/W4399924169"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,49,54,67],"nurse":[4],"rostering":[5],"problem,":[6],"aiming":[7],"to":[8,26,56,90],"create":[9],"an":[10,16],"eight-week":[11],"cyclic":[12],"schedule":[13],"that":[14,61,84],"ensures":[15],"equitable":[17],"distribution":[18],"of":[19,30,96],"work":[20],"hours":[21],"among":[22],"nurses":[23],"while":[24],"adhering":[25],"a":[27],"complex":[28],"set":[29],"constraints.":[31],"Two":[32],"different":[33,85,92],"modeling":[34,86],"approaches":[35],"are":[36],"proposed.":[37],"The":[38,73],"initial":[39],"model,":[40],"incorporating":[41],"strict":[42],"hourly":[43],"constraints,":[44],"proved":[45],"computationally":[46],"infeasible":[47],"using":[48],"CPLEX":[50],"solver.":[51],"By":[52],"reformulating":[53],"constraints":[55],"focus":[57],"on":[58,80],"shift":[59],"counts":[60],"inherently":[62],"satisfy":[63],"total":[64],"working":[65],"hours,":[66],"computational":[68],"complexity":[69],"was":[70],"significantly":[71],"reduced.":[72],"improved":[74],"model":[75],"efficiently":[76],"provides":[77],"optimal":[78],"solutions":[79],"real":[81],"data,":[82],"demonstrating":[83],"techniques":[87],"can":[88],"lead":[89],"vastly":[91],"outcomes":[93],"in":[94],"terms":[95],"solution":[97],"time":[98],"and":[99],"efficiency.":[100]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
