{"id":"https://openalex.org/W7134287260","doi":"https://doi.org/10.48550/arxiv.2603.06260","title":"Learning to Solve Orienteering Problem with Time Windows and Variable Profits","display_name":"Learning to Solve Orienteering Problem with Time Windows and Variable Profits","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134287260","doi":"https://doi.org/10.48550/arxiv.2603.06260"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06260","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034832674","display_name":"Songqun Gao","orcid":"https://orcid.org/0000-0002-2434-8656"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Songqun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128396871","display_name":"Zanxi Ruan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruan, Zanxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128454633","display_name":"Patrick Floor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Floor, Patrick","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055975794","display_name":"Marco Roveri","orcid":"https://orcid.org/0000-0001-9483-3940"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roveri, Marco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128572573","display_name":"Luigi Palopoli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Palopoli, Luigi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045097296","display_name":"Daniele Fontanelli","orcid":"https://orcid.org/0000-0002-5486-9989"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fontanelli, Daniele","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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.8219000101089478,"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":0.8219000101089478,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.06920000165700912,"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"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.042399998754262924,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/orienteering","display_name":"Orienteering","score":0.7408999800682068},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6700000166893005},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5424000024795532},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5267999768257141},{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.4724000096321106},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.41990000009536743},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.3937000036239624},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3806000053882599}],"concepts":[{"id":"https://openalex.org/C513932644","wikidata":"https://www.wikidata.org/wiki/Q29358","display_name":"Orienteering","level":2,"score":0.7408999800682068},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6700000166893005},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6413000226020813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6115999817848206},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5267999768257141},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.4724000096321106},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41990000009536743},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C2776435737","wikidata":"https://www.wikidata.org/wiki/Q7915703","display_name":"Variable neighborhood search","level":3,"score":0.3481000065803528},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.2757999897003174},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C168956720","wikidata":"https://www.wikidata.org/wiki/Q3123181","display_name":"Column generation","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C2780757406","wikidata":"https://www.wikidata.org/wiki/Q465837","display_name":"Skyline","level":2,"score":0.2526000142097473},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.2513999938964844},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06260","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06260","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06260","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":"pmh:doi:10.48550/arxiv.2603.06260","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,97],"orienteering":[1,31],"problem":[2,32],"with":[3,34,50,161,172],"time":[4,19,95],"windows":[5],"and":[6,16,36,61,72,91,110,140,150,176],"variable":[7],"profits":[8],"(OPTWVP)":[9],"is":[10,85,170],"common":[11],"in":[12,65,145],"many":[13],"real-world":[14],"applications":[15],"involves":[17],"continuous":[18,37,62],"variables.":[20,38],"Current":[21],"approaches":[22],"fail":[23],"to":[24,56,87,155],"develop":[25],"an":[26],"efficient":[27,71],"solver":[28],"for":[29,182],"this":[30,40],"variant":[33],"discrete":[35,60],"In":[39,77],"paper,":[41],"we":[42],"propose":[43],"a":[44,81,105,112],"learning-based":[45],"two-stage":[46],"DEcoupled":[47],"discrete-Continuous":[48],"optimization":[49],"Service-time-guided":[51],"Trajectory":[52],"(DeCoST),":[53],"which":[54],"aims":[55],"effectively":[57],"decouple":[58],"the":[59,66,78,89,92,101,121,125,141,167,179],"decision":[63],"variables":[64],"OPTWVP":[67,130],"problem,":[68],"while":[69],"enabling":[70],"learnable":[73],"coordination":[74],"between":[75],"them.":[76],"first":[79],"stage,":[80],"parallel":[82],"decoding":[83],"structure":[84,116],"employed":[86],"predict":[88],"path":[90],"initial":[93],"service":[94,102],"allocation.":[96],"second":[98],"stage":[99],"optimizes":[100],"times":[103],"through":[104],"linear":[106],"programming":[107],"(LP)":[108],"formulation":[109],"provides":[111],"long-horizon":[113],"learning":[114],"of":[115,124,147],"estimation.":[117],"We":[118],"rigorously":[119],"prove":[120],"global":[122],"optimality":[123],"second-stage":[126],"solution.":[127],"Experiments":[128],"on":[129,159],"instances":[131,160],"demonstrate":[132],"that":[133],"DeCoST":[134],"outperforms":[135],"both":[136],"state-of-the-art":[137],"constructive":[138,174],"solvers":[139,175],"latest":[142],"meta-heuristic":[143],"algorithms":[144],"terms":[146],"solution":[148,180],"quality":[149,181],"computational":[151],"efficiency,":[152],"achieving":[153],"up":[154],"6.6x":[156],"inference":[157],"speedup":[158],"fewer":[162],"than":[163],"500":[164],"nodes.":[165],"Moreover,":[166],"proposed":[168],"framework":[169],"compatible":[171],"various":[173],"consistently":[177],"enhances":[178],"OPTWVP.":[183]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-10T00:00:00"}