{"id":"https://openalex.org/W7146988682","doi":"https://doi.org/10.48550/arxiv.2603.29543","title":"Reducing Complexity for Quantum Approaches in Train Load Optimization","display_name":"Reducing Complexity for Quantum Approaches in Train Load Optimization","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7146988682","doi":"https://doi.org/10.48550/arxiv.2603.29543"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.29543","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29543","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.29543","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132641112","display_name":"Zhijie Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tang, Zhijie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132699293","display_name":"Albert Nieto-Morales","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nieto-Morales, Albert","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132600218","display_name":"Arit Kumar Bishwas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bishwas, Arit Kumar","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5132641112"],"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.24549999833106995,"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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.24549999833106995,"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/T11223","display_name":"Maritime Ports and Logistics","score":0.2222999930381775,"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":0.211899995803833,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6797999739646912},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.593999981880188},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.579200029373169},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.4553999900817871},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4523000121116638},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3889999985694885},{"id":"https://openalex.org/keywords/mathematical-model","display_name":"Mathematical model","score":0.3440999984741211}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6797999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6266000270843506},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.593999981880188},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5819000005722046},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.579200029373169},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4523000121116638},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3418000042438507},{"id":"https://openalex.org/C3309909","wikidata":"https://www.wikidata.org/wiki/Q864155","display_name":"Binary decision diagram","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C2781018962","wikidata":"https://www.wikidata.org/wiki/Q5164884","display_name":"Container (type theory)","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C90408235","wikidata":"https://www.wikidata.org/wiki/Q938141","display_name":"Quantum annealing","level":4,"score":0.310699999332428},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2930000126361847},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.29543","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29543","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.29543","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.29543","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Efficiently":[0],"planning":[1],"container":[2],"loads":[3],"onto":[4],"trains":[5],"is":[6,100,158,180],"a":[7,54,75,124,132,136,161,190],"computationally":[8],"challenging":[9],"combinatorial":[10],"optimization":[11],"problem,":[12],"central":[13],"to":[14,30,39,70,123,139],"logistics":[15],"and":[16,32,53,85,118,150,192],"supply":[17],"chain":[18],"management.":[19],"A":[20],"primary":[21],"source":[22],"of":[23,56,148,154],"this":[24,47,79],"complexity":[25],"arises":[26],"from":[27,78],"the":[28,90,97,104,112,142,146],"need":[29,113],"model":[31,128,138,179],"reduce":[33],"rehandle":[34,98,116],"operations-unproductive":[35],"crane":[36],"moves":[37],"required":[38],"access":[40],"blocked":[41],"containers.":[42],"Conventional":[43],"mathematical":[44,87],"formulations":[45],"address":[46],"by":[48],"introducing":[49],"explicit":[50],"binary":[51],"variables":[52,117,149],"web":[55],"logical":[57],"constraints":[58],"for":[59,89,114,170,195],"each":[60],"potential":[61],"rehandle,":[62],"resulting":[63],"in":[64,127,145],"large-scale":[65],"models":[66],"that":[67,177],"are":[68],"difficult":[69],"solve.":[71],"This":[72,107],"paper":[73],"presents":[74],"fundamental":[76],"departure":[77],"paradigm.":[80],"We":[81,130],"introduce":[82],"an":[83],"innovative":[84],"compact":[86,156],"formulation":[88,157],"Train":[91],"Load":[92],"Optimization":[93],"(TLO)":[94],"problem":[95,172],"where":[96],"cost":[99],"calculated":[101],"implicitly":[102],"within":[103],"objective":[105],"function.":[106],"novel":[108],"approach":[109],"helps":[110],"prevent":[111],"dedicated":[115],"their":[119],"associated":[120],"constraints,":[121],"leading":[122],"dramatic":[125],"reduction":[126,144],"size.":[129],"provide":[131],"formal":[133],"comparison":[134],"against":[135],"conventional":[137],"analytically":[140],"demonstrate":[141],"significant":[143],"number":[147],"constraints.":[151],"The":[152,174],"efficacy":[153],"our":[155,178],"assessed":[159],"through":[160],"simulated":[162],"annealing":[163],"metaheuristic,":[164],"which":[165],"finds":[166],"high-quality":[167],"loading":[168],"plans":[169],"various":[171],"instances.":[173],"results":[175],"confirm":[176],"not":[181],"only":[182],"more":[183],"parsimonious":[184],"but":[185],"also":[186],"practically":[187],"effective,":[188],"offering":[189],"scalable":[191],"powerful":[193],"tool":[194],"modern":[196],"rail":[197],"logistics.":[198]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}