{"id":"https://openalex.org/W2963232841","doi":"https://doi.org/10.1609/aaai.v33i01.33017876","title":"Randomized Strategies for Robust Combinatorial Optimization","display_name":"Randomized Strategies for Robust Combinatorial Optimization","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2963232841","doi":"https://doi.org/10.1609/aaai.v33i01.33017876","mag":"2963232841"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33017876","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017876","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v33i01.33017876","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025634820","display_name":"Yasushi Kawase","orcid":"https://orcid.org/0000-0001-5626-779X"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasushi Kawase","raw_affiliation_strings":["Tokyo Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040863107","display_name":"Hanna Sumita","orcid":"https://orcid.org/0000-0003-4005-3206"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hanna Sumita","raw_affiliation_strings":["Tokyo Metropolitan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.4946,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.9491018,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"33","issue":"01","first_page":"7876","last_page":"7883"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12176","display_name":"Optimization and Packing Problems","score":0.9887999892234802,"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":0.9887999892234802,"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/T12288","display_name":"Optimization and Search Problems","score":0.9765999913215637,"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/T11106","display_name":"Data Management and Algorithms","score":0.9595999717712402,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/submodular-set-function","display_name":"Submodular set function","score":0.7415005564689636},{"id":"https://openalex.org/keywords/knapsack-problem","display_name":"Knapsack problem","score":0.6939345598220825},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6505697965621948},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.5947434306144714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5062586665153503},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.45788896083831787},{"id":"https://openalex.org/keywords/randomized-algorithm","display_name":"Randomized algorithm","score":0.441798597574234},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.42678511142730713},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.4252646565437317},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.42500293254852295},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.41178637742996216},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4106256365776062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39593109488487244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2890239357948303}],"concepts":[{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.7415005564689636},{"id":"https://openalex.org/C113138325","wikidata":"https://www.wikidata.org/wiki/Q864457","display_name":"Knapsack problem","level":2,"score":0.6939345598220825},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6505697965621948},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.5947434306144714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5062586665153503},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.45788896083831787},{"id":"https://openalex.org/C128669082","wikidata":"https://www.wikidata.org/wiki/Q583461","display_name":"Randomized algorithm","level":2,"score":0.441798597574234},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.42678511142730713},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4252646565437317},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.42500293254852295},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.41178637742996216},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4106256365776062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39593109488487244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2890239357948303},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33017876","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017876","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4786","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4786","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4786/4664","source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33017876","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017876","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1788628092","display_name":null,"funder_award_id":"JP17K12646","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3948853704","display_name":null,"funder_award_id":"KAKENHI Grant Number JP16K16005","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G648459597","display_name":null,"funder_award_id":"JPMJER1201","funder_id":"https://openalex.org/F4320338112","funder_display_name":"Exploratory Research for Advanced Technology"},{"id":"https://openalex.org/G6782693327","display_name":null,"funder_award_id":"JP16K16005","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338112","display_name":"Exploratory Research for Advanced Technology","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W568984285","https://openalex.org/W1497312391","https://openalex.org/W1498671329","https://openalex.org/W1576820654","https://openalex.org/W1600999481","https://openalex.org/W1601835603","https://openalex.org/W1981351071","https://openalex.org/W1994753237","https://openalex.org/W1997684383","https://openalex.org/W2009786555","https://openalex.org/W2011039300","https://openalex.org/W2016428812","https://openalex.org/W2028589351","https://openalex.org/W2031666601","https://openalex.org/W2033885045","https://openalex.org/W2053381548","https://openalex.org/W2065139435","https://openalex.org/W2079266301","https://openalex.org/W2080656989","https://openalex.org/W2094067695","https://openalex.org/W2106887613","https://openalex.org/W2113437680","https://openalex.org/W2151450177","https://openalex.org/W2158557760","https://openalex.org/W2179494254","https://openalex.org/W2199299606","https://openalex.org/W2293386763","https://openalex.org/W2482469685","https://openalex.org/W2500139799","https://openalex.org/W2583519108","https://openalex.org/W2621717961","https://openalex.org/W2729365008","https://openalex.org/W2776000100","https://openalex.org/W2804205100","https://openalex.org/W2809072130","https://openalex.org/W3158732259","https://openalex.org/W4300645277","https://openalex.org/W6636482698","https://openalex.org/W6654466127","https://openalex.org/W6663912604","https://openalex.org/W6666622825","https://openalex.org/W6670678479","https://openalex.org/W6687643950","https://openalex.org/W6692783503","https://openalex.org/W6724212191","https://openalex.org/W6740200382","https://openalex.org/W6759357910","https://openalex.org/W7039610924"],"related_works":["https://openalex.org/W2950365512","https://openalex.org/W1608444752","https://openalex.org/W3204684126","https://openalex.org/W2098281589","https://openalex.org/W2062310236","https://openalex.org/W3013568067","https://openalex.org/W3155769677","https://openalex.org/W4299354108","https://openalex.org/W3118541900","https://openalex.org/W4313343266"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,18,81,137,246],"study":[4],"the":[5,47,52,57,79,95,120,161,171,196,251,259,263],"following":[6],"robust":[7],"optimization":[8],"problem.":[9,265],"Given":[10],"an":[11,20,25,105,131,186,227],"independence":[12,132],"system":[13,133],"and":[14,23,75,110,153,212],"candidate":[15],"objective":[16,29,54,98,121,207,252],"functions,":[17],"choose":[19],"independent":[21,48],"set,":[22],"then":[24,111],"adversary":[26],"chooses":[27],"one":[28,184],"function,":[30],"knowing":[31],"our":[32,217,244],"choice.":[33],"The":[34,123,155,167],"goal":[35],"is":[36,62,93,158,198],"to":[37,194,199,258],"find":[38],"a":[39,43,113,128,142,146,177,201,220,231],"randomized":[40],"strategy":[41,109],"(i.e.,":[42],"probability":[44],"distribution":[45],"over":[46],"sets)":[49],"that":[50,216],"maximizes":[51],"expected":[53],"value":[55],"in":[56,64,240],"worst":[58],"case.":[59],"This":[60,236],"problem":[61],"fundamental":[63],"wide":[65],"areas":[66],"such":[67],"as":[68],"artificial":[69],"intelligence,":[70],"machine":[71],"learning,":[72],"game":[73],"theory":[74],"optimization.":[76],"To":[77],"solve":[78],"problem,":[80],"propose":[82],"two":[83],"types":[84],"of":[85,119,130,170],"schemes":[86],"for":[87,94,141,206,230,262],"designing":[88],"approximation":[89,124,139,180,238,248],"algorithms.":[90],"One":[91],"scheme":[92,157,218],"case":[96],"when":[97,250],"functions":[99,208,253],"are":[100,254],"linear.":[101],"It":[102],"first":[103],"finds":[104],"approximately":[106],"optimal":[107],"aggregated":[108],"retrieves":[112],"desired":[114],"solution":[115,223],"with":[116,185,209],"little":[117],"loss":[118],"value.":[122],"ratio":[125],"depends":[126],"on":[127,160],"relaxation":[129],"polytope.":[134],"As":[135],"applications,":[136],"provide":[138,247],"algorithms":[140,249],"knapsack":[143,264],"constraint":[144],"or":[145,256],"matroid":[147],"intersection":[148],"by":[149,234],"developing":[150],"appropriate":[151],"relaxations":[152],"retrievals.":[154],"other":[156],"based":[159],"multiplicative":[162,179],"weights":[163],"update":[164],"(MWU)":[165],"method.":[166],"direct":[168],"application":[169],"MWU":[172],"method":[173],"does":[174],"not":[175],"yield":[176,183],"strict":[178],"algorithm":[181,229],"but":[182],"additional":[187],"additive":[188],"error":[189],"term.":[190],"A":[191],"key":[192],"technique":[193],"overcome":[195],"issue":[197],"introduce":[200],"new":[202],"concept":[203],"called":[204],"(\u03b7,\u03b3)-reductions":[205],"parameters":[210],"\u03b7":[211],"\u03b3.":[213],"We":[214],"show":[215],"outputs":[219],"nearly":[221],"\u03b1-approximate":[222],"if":[224],"there":[225],"exists":[226],"\u03b1-approximation":[228],"subproblem":[232],"defined":[233],"(\u03b7,\u03b3)-reductions.":[235],"improves":[237],"ratios":[239],"previous":[241],"results.":[242],"Using":[243],"result,":[245],"submodular":[255],"correspond":[257],"cardinality":[260],"robustness":[261]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}