{"id":"https://openalex.org/W4309532043","doi":"https://doi.org/10.1109/kse56063.2022.9953796","title":"An Iterated Local Search for the Talent Scheduling Problem with Location Costs","display_name":"An Iterated Local Search for the Talent Scheduling Problem with Location Costs","publication_year":2022,"publication_date":"2022-10-19","ids":{"openalex":"https://openalex.org/W4309532043","doi":"https://doi.org/10.1109/kse56063.2022.9953796"},"language":"en","primary_location":{"id":"doi:10.1109/kse56063.2022.9953796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse56063.2022.9953796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Knowledge and Systems Engineering (KSE)","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/A5079687625","display_name":"Thu Trang Hoa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124651","display_name":"Phenikaa University","ror":"https://ror.org/03anxx281","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210124651"]}],"countries":["VN"],"is_corresponding":true,"raw_author_name":"Thu Trang Hoa","raw_affiliation_strings":["Phenikaa University,ORLab, Faculty of Computer Science,Hanoi,Vietnam","ORLab, Faculty of Computer Science, Phenikaa University, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Phenikaa University,ORLab, Faculty of Computer Science,Hanoi,Vietnam","institution_ids":["https://openalex.org/I4210124651"]},{"raw_affiliation_string":"ORLab, Faculty of Computer Science, Phenikaa University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210124651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5120863438","display_name":"Minh Nguyen","orcid":"https://orcid.org/0000-0003-0316-8645"},"institutions":[{"id":"https://openalex.org/I4210124651","display_name":"Phenikaa University","ror":"https://ror.org/03anxx281","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210124651"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Minh Anh Nguyen","raw_affiliation_strings":["Phenikaa University,ORLab, Faculty of Computer Science,Hanoi,Vietnam","ORLab, Faculty of Computer Science, Phenikaa University, Hanoi, Vietnam"],"affiliations":[{"raw_affiliation_string":"Phenikaa University,ORLab, Faculty of Computer Science,Hanoi,Vietnam","institution_ids":["https://openalex.org/I4210124651"]},{"raw_affiliation_string":"ORLab, Faculty of Computer Science, Phenikaa University, Hanoi, Vietnam","institution_ids":["https://openalex.org/I4210124651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5079687625"],"corresponding_institution_ids":["https://openalex.org/I4210124651"],"apc_list":null,"apc_paid":null,"fwci":0.1334,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54204972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9991000294685364,"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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9972000122070312,"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/T12288","display_name":"Optimization and Search Problems","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7084164619445801},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6942154169082642},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6787947416305542},{"id":"https://openalex.org/keywords/iterated-local-search","display_name":"Iterated local search","score":0.6390869617462158},{"id":"https://openalex.org/keywords/time-horizon","display_name":"Time horizon","score":0.6342369318008423},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5946850180625916},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5612128973007202},{"id":"https://openalex.org/keywords/integer-programming","display_name":"Integer programming","score":0.5276331305503845},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.5170326828956604},{"id":"https://openalex.org/keywords/tabu-search","display_name":"Tabu search","score":0.47469109296798706},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.4513397216796875},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.2872122526168823},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17825531959533691},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15323904156684875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7084164619445801},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6942154169082642},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6787947416305542},{"id":"https://openalex.org/C124145224","wikidata":"https://www.wikidata.org/wiki/Q6094397","display_name":"Iterated local search","level":3,"score":0.6390869617462158},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.6342369318008423},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5946850180625916},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5612128973007202},{"id":"https://openalex.org/C56086750","wikidata":"https://www.wikidata.org/wiki/Q6042592","display_name":"Integer programming","level":2,"score":0.5276331305503845},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.5170326828956604},{"id":"https://openalex.org/C123370116","wikidata":"https://www.wikidata.org/wiki/Q1424540","display_name":"Tabu search","level":2,"score":0.47469109296798706},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.4513397216796875},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.2872122526168823},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17825531959533691},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15323904156684875},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":1,"locations":[{"id":"doi:10.1109/kse56063.2022.9953796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse56063.2022.9953796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309617","display_name":"National Foundation for Science and Technology Development","ror":"https://ror.org/04rw64z44"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W98694689","https://openalex.org/W1584243346","https://openalex.org/W1816779164","https://openalex.org/W1967715706","https://openalex.org/W1971128369","https://openalex.org/W1973308356","https://openalex.org/W1988292213","https://openalex.org/W2004115473","https://openalex.org/W2021793830","https://openalex.org/W2088108448","https://openalex.org/W2141119792","https://openalex.org/W2153633961","https://openalex.org/W2896649370","https://openalex.org/W3121748795","https://openalex.org/W3140168407","https://openalex.org/W6603976772"],"related_works":["https://openalex.org/W2937685542","https://openalex.org/W2935342279","https://openalex.org/W1608676749","https://openalex.org/W1968740415","https://openalex.org/W2567474168","https://openalex.org/W2535266198","https://openalex.org/W2036813338","https://openalex.org/W2123115451","https://openalex.org/W1533229056","https://openalex.org/W3082661417"],"abstract_inverted_index":{"The":[0,77,170],"talent":[1,42,167],"scheduling":[2,43,168],"problem":[3,44,118],"seeks":[4],"to":[5,80,134],"determine":[6],"the":[7,13,17,28,41,50,64,74,82,88,96,111,117,166,185],"movie":[8,33],"shooting":[9,83],"sequence":[10,84],"that":[11,45,63,94,145,180],"minimizes":[12,95],"total":[14,97],"cost":[15,29,66],"of":[16,27,30,40,52,165,172,195],"actors":[18],"involved,":[19],"which":[20,128],"usually":[21],"accounts":[22],"for":[23,67,91,161],"a":[24,68,120,156,190],"significant":[25],"portion":[26],"any":[31],"real-world":[32],"production.":[34],"This":[35],"paper":[36],"introduces":[37],"an":[38,140],"extension":[39],"takes":[46],"into":[47],"account":[48],"both":[49,196],"costs":[51],"filming":[53,69],"locations":[54],"and":[55,101,199],"actors.":[56],"To":[57],"better":[58],"capture":[59],"reality,":[60],"we":[61,154],"consider":[62],"rental":[65],"location":[70,102],"can":[71,131,146,183],"vary":[72],"across":[73],"planning":[75,112],"horizon.":[76,113],"objective":[78],"is":[79,151],"find":[81],"as":[85,87,119],"well":[86],"start":[89],"date":[90],"each":[92],"scene":[93],"cost,":[98],"including":[99],"actor":[100],"costs,":[103],"while":[104],"ensuring":[105],"all":[106],"scenes":[107],"are":[108],"completed":[109],"within":[110],"We":[114],"first":[115],"formulate":[116],"mixed":[121],"integer":[122],"linear":[123],"programming":[124],"(MILP)":[125],"model,":[126],"from":[127],"small":[129],"instances":[130,150,178],"be":[132],"solved":[133,188],"optimality":[135],"by":[136,189],"MILP":[137,186],"solvers.":[138],"Next,":[139],"iterated":[141],"local":[142],"search":[143],"heuristic":[144,182],"efficiently":[147],"solve":[148],"larger":[149],"developed.":[152],"Then":[153],"provide":[155],"new":[157,163,176],"benchmark":[158,177],"data":[159],"set":[160],"our":[162,181],"variance":[164],"problem.":[169],"results":[171],"computational":[173],"experiments":[174],"upon":[175],"suggest":[179],"outperform":[184],"model":[187],"commercial":[191],"solver":[192],"in":[193],"terms":[194],"solution":[197],"quality":[198],"runtime.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
