{"id":"https://openalex.org/W7160447558","doi":"https://doi.org/10.48550/arxiv.2605.03842","title":"SOAR: Real-Time Joint Optimization of Order Allocation and Robot Scheduling in Robotic Mobile Fulfillment Systems","display_name":"SOAR: Real-Time Joint Optimization of Order Allocation and Robot Scheduling in Robotic Mobile Fulfillment Systems","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160447558","doi":"https://doi.org/10.48550/arxiv.2605.03842"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.03842","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03842","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.2605.03842","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037394880","display_name":"Yibang Tang","orcid":"https://orcid.org/0009-0001-4820-9511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yibang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135487096","display_name":"Yifan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135471422","display_name":"Jingyuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jingyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135495131","display_name":"Junhua Chen","orcid":"https://orcid.org/0000-0002-0947-6879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Junhua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135428535","display_name":"Zhen Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Zhen","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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.15970000624656677,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.15970000624656677,"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":0.0908999964594841,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.08079999685287476,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5575000047683716},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5443999767303467},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.49300000071525574},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4855000078678131},{"id":"https://openalex.org/keywords/soar","display_name":"Soar","score":0.4779999852180481},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.4607999920845032},{"id":"https://openalex.org/keywords/dynamic-priority-scheduling","display_name":"Dynamic priority scheduling","score":0.4246000051498413},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.40720000863075256},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.39010000228881836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6656000018119812},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5575000047683716},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5443999767303467},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.49300000071525574},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4855000078678131},{"id":"https://openalex.org/C17305859","wikidata":"https://www.wikidata.org/wiki/Q382944","display_name":"Soar","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.4607999920845032},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4388999938964844},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.4246000051498413},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.40720000863075256},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35260000824928284},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.34150001406669617},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C74222875","wikidata":"https://www.wikidata.org/wiki/Q16000312","display_name":"Robot kinematics","level":4,"score":0.257099986076355},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.25589999556541443},{"id":"https://openalex.org/C22171661","wikidata":"https://www.wikidata.org/wiki/Q1074380","display_name":"Stochastic game","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.03842","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03842","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.2605.03842","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.03842","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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5890384316444397}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Robotic":[0],"Mobile":[1],"Fulfillment":[2],"Systems":[3],"(RMFS)":[4],"rely":[5,59],"on":[6,60,163],"mobile":[7],"robots":[8],"for":[9,69,86],"automated":[10],"inventory":[11],"transportation,":[12],"coordinating":[13],"order":[14,92,104,183],"allocation":[15,93],"and":[16,33,94,142,165,181,198],"robot":[17,95],"scheduling":[18,96,123],"to":[19,29,49,120,126,137,154],"enhance":[20],"warehousing":[21],"efficiency.":[22],"However,":[23],"optimizing":[24],"RMFS":[25],"is":[26,207],"challenging":[27],"due":[28],"strict":[30],"real-time":[31,87],"constraints":[32],"the":[34,44,53,118,139],"strong":[35],"coupling":[36],"of":[37,55],"multi-phase":[38],"decisions.":[39],"Existing":[40],"methods":[41],"either":[42],"decompose":[43],"problem":[45],"into":[46,97],"isolated":[47],"sub-tasks":[48],"guarantee":[50],"responsiveness":[51],"at":[52,209],"cost":[54],"global":[56,63,177],"optimality,":[57],"or":[58],"computationally":[61],"expensive":[62],"optimization":[64],"models":[65],"that":[66,174],"are":[67],"unsuitable":[68],"dynamic":[70],"industrial":[71,167],"environments.":[72,204],"To":[73],"bridge":[74],"this":[75,110],"gap,":[76],"we":[77,131,148],"propose":[78],"SOAR,":[79],"a":[80,98,133,150],"unified":[81,99],"Deep":[82],"Reinforcement":[83],"Learning":[84],"framework":[85],"joint":[88],"optimization.":[89],"SOAR":[90,175],"transforms":[91],"process":[100],"by":[101,179,186],"utilizing":[102],"soft":[103],"allocations":[105],"as":[106,111],"observations.":[107],"We":[108],"formulate":[109],"an":[112],"Event-Driven":[113],"Markov":[114],"Decision":[115],"Process,":[116],"enabling":[117],"agent":[119],"perform":[121],"simultaneous":[122],"in":[124,158,169,202],"response":[125],"asynchronous":[127],"system":[128],"events.":[129],"Technically,":[130],"employ":[132],"Heterogeneous":[134],"Graph":[135],"Transformer":[136],"encode":[138],"warehouse":[140],"state":[141],"integrate":[143],"phased":[144],"domain":[145],"knowledge.":[146],"Additionally,":[147],"incorporate":[149],"reward":[151],"shaping":[152],"strategy":[153],"address":[155],"sparse":[156],"feedback":[157],"long-horizon":[159],"tasks.":[160],"Extensive":[161],"experiments":[162],"synthetic":[164],"real-world":[166],"datasets,":[168],"collaboration":[170],"with":[171,188],"Geekplus,":[172],"demonstrate":[173],"reduces":[176],"makespan":[178],"7.5\\%":[180],"average":[182],"completion":[184],"time":[185],"15.4\\%":[187],"sub-100ms":[189],"latency.":[190],"Furthermore,":[191],"sim-to-real":[192],"deployment":[193],"confirms":[194],"its":[195],"practical":[196],"viability":[197],"significant":[199],"performance":[200],"gains":[201],"production":[203],"The":[205],"code":[206],"available":[208],"https://github.com/200815147/SOAR.":[210]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-07T00:00:00"}
