{"id":"https://openalex.org/W7154945451","doi":"https://doi.org/10.48550/arxiv.2604.16149","title":"Fast and Memory Efficient Multimodal Journey Planning with Delays","display_name":"Fast and Memory Efficient Multimodal Journey Planning with Delays","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154945451","doi":"https://doi.org/10.48550/arxiv.2604.16149"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16149","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16149","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16149","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126722103","display_name":"Denys Katkalo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katkalo, Denys","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114617330","display_name":"Andrii Rohovyi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohovyi, Andrii","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134037728","display_name":"Toby Walsh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Walsh, Toby","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.5131000280380249,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.5131000280380249,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.06469999998807907,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.06019999831914902,"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/speedup","display_name":"Speedup","score":0.9139000177383423},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43299999833106995},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38109999895095825},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.36169999837875366}],"concepts":[{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.9139000177383423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7592999935150146},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43299999833106995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42739999294281006},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30889999866485596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3012000024318695},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2840000092983246},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.272599995136261}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16149","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16149","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.16149","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16149","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.6550595760345459,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"State-of-the-art":[0],"multimodal":[1],"journey-planning":[2],"algorithms,":[3,37],"such":[4],"as":[5,79],"ULTRA,":[6],"have":[7],"recently":[8],"been":[9],"adapted":[10],"to":[11,22,34],"account":[12],"for":[13],"delays.":[14],"In":[15,58],"this":[16,20,32],"work,":[17],"we":[18,62],"extend":[19],"approach":[21],"be":[23],"more":[24],"memory-efficient,":[25],"faster,":[26],"and":[27,40],"accurate.":[28],"We":[29,42,70],"also":[30,71],"adapt":[31],"framework":[33],"other":[35],"state-of-the-art":[36],"like":[38],"CSA":[39],"RAPTOR.":[41],"demonstrate":[43],"a":[44],"speedup":[45,65],"of":[46],"1.9-4.2x":[47],"over":[48],"existing":[49],"algorithms":[50],"in":[51],"the":[52,59,80],"single-objective":[53],"search":[54],"(earliest":[55],"arrival":[56],"time).":[57],"bicriteria":[60],"setting,":[61],"achieve":[63],"competitive":[64],"results":[66],"but":[67],"greater":[68],"accuracy.":[69],"find":[72],"that":[73],"our":[74],"method":[75],"scales":[76],"much":[77],"better":[78],"delay":[81],"buffer":[82],"Delta":[83],"increases.":[84]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-21T00:00:00"}