{"id":"https://openalex.org/W4412597742","doi":"https://doi.org/10.7148/2025-0462","title":"Multi-Objective Optimization For Employee Carpooling Using The IMGAMO Algorithm And Baldwin Effect","display_name":"Multi-Objective Optimization For Employee Carpooling Using The IMGAMO Algorithm And Baldwin Effect","publication_year":2025,"publication_date":"2025-06-24","ids":{"openalex":"https://openalex.org/W4412597742","doi":"https://doi.org/10.7148/2025-0462"},"language":"en","primary_location":{"id":"doi:10.7148/2025-0462","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2025-0462","pdf_url":"http://www.scs-europe.net/dlib/2025/ecms2025acceptedpapers/0462_simo_ecms2025_0055.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://www.scs-europe.net/dlib/2025/ecms2025acceptedpapers/0462_simo_ecms2025_0055.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119053209","display_name":"Jarosz Pawel","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jarosz Pawel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Marszalek Adam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marszalek Adam","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119053209"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17743989,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"462","last_page":"468"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T11942","display_name":"Transportation and Mobility Innovations","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6435627341270447},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.5035783648490906},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3831939995288849},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36011627316474915},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17033758759498596}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6435627341270447},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.5035783648490906},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3831939995288849},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36011627316474915},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17033758759498596}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.7148/2025-0462","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2025-0462","pdf_url":"http://www.scs-europe.net/dlib/2025/ecms2025acceptedpapers/0462_simo_ecms2025_0055.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.7148/2025-0462","is_oa":true,"landing_page_url":"https://doi.org/10.7148/2025-0462","pdf_url":"http://www.scs-europe.net/dlib/2025/ecms2025acceptedpapers/0462_simo_ecms2025_0055.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412597742.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4366549320","https://openalex.org/W4287863136","https://openalex.org/W3006015132","https://openalex.org/W2965078190","https://openalex.org/W4408464351","https://openalex.org/W2140656843","https://openalex.org/W3040644038","https://openalex.org/W3203633096"],"abstract_inverted_index":{"The":[0,110],"primary":[1],"objective":[2,142],"of":[3,12,22,30,52,74,83,134,141],"the":[4,9,19,28,44,50,75,98,132,139],"carpooling":[5,76],"task,":[6],"which":[7],"involves":[8],"shared":[10],"use":[11],"vehicles":[13],"for":[14,39,87],"transportation,":[15],"is":[16],"to":[17,26,89,94],"determine":[18],"optimal":[20],"configuration":[21],"passengers":[23,137],"and":[24,57,63,65,136,138],"drivers":[25,135],"maximize":[27],"number":[29,51,133,140],"transported":[31],"people":[32],"Various":[33],"optimization":[34,123],"criteria":[35],"have":[36],"been":[37,108,114],"defined":[38],"this":[40,96],"problem,":[41,77,97],"including":[42,129],"minimizing":[43],"travel":[45],"distance":[46],"or":[47],"time,":[48],"maximizing":[49],"passengers,":[53],"reducing":[54],"CO2":[55],"emissions":[56],"carbon":[58],"footprint,":[59],"enhancing":[60],"user":[61],"comfort":[62],"safety,":[64],"many":[66],"others.":[67],"This":[68],"study":[69],"presents":[70],"a":[71,84],"modified":[72],"version":[73],"focusing":[78],"on":[79],"ridesharing":[80],"among":[81],"employees":[82],"specific":[85],"company":[86],"commuting":[88],"its":[90],"headquarters.":[91],"In":[92],"order":[93],"solve":[95],"IMGAMO":[99],"algorithm":[100],"combined":[101],"with":[102,119],"local":[103],"search":[104],"(Baldwin":[105],"effect)":[106],"has":[107,113],"proposed.":[109],"algorithm\u2019s":[111],"effectiveness":[112],"validated":[115],"by":[116],"comparing":[117],"it":[118],"traditional":[120],"evolutionary":[121],"multi-objective":[122],"algorithms":[124],"under":[125],"different":[126],"problem":[127],"configurations,":[128],"variations":[130],"in":[131],"functions.":[143]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
