{"id":"https://openalex.org/W7155223993","doi":"https://doi.org/10.48550/arxiv.2604.19271","title":"Effective Traveling for Metric Instances of the Traveling Thief Problem","display_name":"Effective Traveling for Metric Instances of the Traveling Thief Problem","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155223993","doi":"https://doi.org/10.48550/arxiv.2604.19271"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19271","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.19271","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069105734","display_name":"Jan Eube","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eube, Jan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077814737","display_name":"Kelin Luo","orcid":"https://orcid.org/0000-0003-2006-0601"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Kelin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134308518","display_name":"Aneta Neumann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neumann, Aneta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134359756","display_name":"Frank Neumann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neumann, Frank","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034122679","display_name":"Heiko R\u00f6glin","orcid":"https://orcid.org/0009-0006-8438-3986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R\u00f6glin, Heiko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T12176","display_name":"Optimization and Packing Problems","score":0.6866000294685364,"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/T12176","display_name":"Optimization and Packing Problems","score":0.6866000294685364,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.21060000360012054,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.03009999915957451,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/knapsack-problem","display_name":"Knapsack problem","score":0.8436999917030334},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.675599992275238},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6687999963760376},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4900999963283539},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45500001311302185},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.44609999656677246},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.41110000014305115},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.3896999955177307},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.38359999656677246}],"concepts":[{"id":"https://openalex.org/C113138325","wikidata":"https://www.wikidata.org/wiki/Q864457","display_name":"Knapsack problem","level":2,"score":0.8436999917030334},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.7017999887466431},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.675599992275238},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6687999963760376},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4659000039100647},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42969998717308044},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.41110000014305115},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C2780897414","wikidata":"https://www.wikidata.org/wiki/Q7600592","display_name":"Star (game theory)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33660000562667847},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C94569963","wikidata":"https://www.wikidata.org/wiki/Q5165487","display_name":"Continuous knapsack problem","level":3,"score":0.3280999958515167},{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C17722475","wikidata":"https://www.wikidata.org/wiki/Q3406279","display_name":"Change-making problem","level":4,"score":0.31839999556541443},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C52692508","wikidata":"https://www.wikidata.org/wiki/Q1333872","display_name":"Combinatorial optimization","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C108005400","wikidata":"https://www.wikidata.org/wiki/Q1305598","display_name":"Facility location problem","level":2,"score":0.25999999046325684}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19271","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.19271","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19271","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4372476637363434,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,32,234],"Traveling":[1,23],"Thief":[2],"Problem":[3,25,30],"(TTP)":[4],"is":[5,75,162],"a":[6,44,76,105,114,166,188,192,210],"multi-component":[7],"optimization":[8],"problem":[9,161,186],"that":[10,159,237],"captures":[11],"the":[12,21,28,39,53,58,70,89,99,118,125,151,160,185,217,245,255,261,264],"interplay":[13],"between":[14],"routing":[15],"and":[16,27,43,131,137,169],"packing":[17,107],"decisions":[18],"by":[19,223,229,253,271],"combining":[20],"classical":[22],"Salesperson":[24],"(TSP)":[26],"Knapsack":[29],"(KP).":[31],"TTP":[33,103,206],"has":[34],"gained":[35],"significant":[36],"attention":[37],"in":[38,63,65],"evolutionary":[40],"computation":[41],"literature":[42],"wide":[45],"range":[46],"of":[47,60,67,102,117,128,220,247,263],"approaches":[48,222],"have":[49],"been":[50],"developed":[51],"over":[52],"last":[54],"10":[55],"years.":[56],"Judging":[57],"performance":[59],"these":[61],"algorithms":[62,173],"particular":[64],"terms":[66],"how":[68,133],"close":[69],"get":[71],"to":[72,88,209,226,242],"optimal":[73],"solutions":[74,227,248,269],"very":[77],"challenging":[78,91],"task":[79,112],"as":[80,113],"effective":[81],"exact":[82],"methods":[83,239],"are":[84,240],"not":[85],"available":[86],"due":[87],"highly":[90],"traveling":[92,256],"component.":[93],"In":[94],"this":[95,111],"paper,":[96],"we":[97,178],"study":[98],"tour-optimization":[100],"component":[101,266],"under":[104,187],"fixed":[106],"plan.":[108],"We":[109,143,196],"formulate":[110],"weighted":[115],"variant":[116],"TSP,":[119],"where":[120],"travel":[121,265],"costs":[122],"depend":[123],"on":[124,165,204],"cumulative":[126],"weight":[127],"collected":[129],"items,":[130],"investigate":[132],"different":[134],"distance":[135],"metrics":[136],"cost":[138,156,194],"functions":[139],"affect":[140],"computational":[141],"complexity.":[142],"present":[144],"an":[145,181],"$(O(n^2))$-time":[146],"dynamic":[147],"programming":[148],"algorithm":[149,183],"for":[150,174,184,249,267],"path":[152,211],"metric":[153,190],"with":[154,191,201],"general":[155,189],"functions,":[157],"prove":[158],"NP-hard":[163],"even":[164],"star":[167,175],"metric,":[168],"develop":[170,180],"constant-factor":[171],"approximation":[172,182],"metrics.":[176],"Finally,":[177],"also":[179],"linear":[193],"function.":[195],"complement":[197],"our":[198,221,238],"theoretical":[199],"results":[200,215,235],"experimental":[202,214],"evaluations":[203],"standard":[205],"instances":[207,252],"adjusted":[208],"metric.":[212],"Our":[213],"demonstrate":[216],"practical":[218],"effectiveness":[219],"comparing":[224],"it":[225],"produced":[228],"popular":[230],"iterative":[231,272],"search":[232,273],"algorithms.":[233],"show":[236],"able":[241],"significantly":[243],"improve":[244],"quality":[246],"some":[250],"benchmark":[251],"optimizing":[254],"part":[257],"while":[258],"pointing":[259],"out":[260],"optimality":[262],"other":[268],"obtained":[270],"methods.":[274]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-23T00:00:00"}
