{"id":"https://openalex.org/W3207873971","doi":"https://doi.org/10.1145/3469801","title":"Efficient Computation of Probabilistic Dominance in Multi-objective Optimization","display_name":"Efficient Computation of Probabilistic Dominance in Multi-objective Optimization","publication_year":2021,"publication_date":"2021-10-13","ids":{"openalex":"https://openalex.org/W3207873971","doi":"https://doi.org/10.1145/3469801","mag":"3207873971"},"language":"en","primary_location":{"id":"doi:10.1145/3469801","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469801","pdf_url":null,"source":{"id":"https://openalex.org/S4210221532","display_name":"ACM Transactions on Evolutionary Learning and Optimization","issn_l":"2688-299X","issn":["2688-299X","2688-3007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Evolutionary Learning and Optimization","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103284241","display_name":"Faramarz Khosravi","orcid":"https://orcid.org/0000-0001-9032-4751"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Faramarz Khosravi","raw_affiliation_strings":["Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049118899","display_name":"Alexander Ra\u00df","orcid":"https://orcid.org/0000-0003-1274-6398"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Rass","raw_affiliation_strings":["Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076672029","display_name":"J\u00fcrgen Teich","orcid":"https://orcid.org/0000-0001-6285-5862"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J\u00fcrgen Teich","raw_affiliation_strings":["Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103284241"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":0.2959,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62506697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"1","issue":"4","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":1.0,"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"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7118586897850037},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6814084053039551},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.6490365862846375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6158983111381531},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5851138830184937},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5779500007629395},{"id":"https://openalex.org/keywords/stochastic-optimization","display_name":"Stochastic optimization","score":0.5404447317123413},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.5026113986968994},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.4744364321231842},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.47044649720191956},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.44403499364852905},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4309755563735962},{"id":"https://openalex.org/keywords/continuous-optimization","display_name":"Continuous optimization","score":0.41825270652770996},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2388293445110321},{"id":"https://openalex.org/keywords/multi-swarm-optimization","display_name":"Multi-swarm optimization","score":0.22220396995544434},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19671404361724854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1723208725452423}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7118586897850037},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6814084053039551},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.6490365862846375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158983111381531},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5851138830184937},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5779500007629395},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.5404447317123413},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.5026113986968994},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.4744364321231842},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.47044649720191956},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.44403499364852905},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4309755563735962},{"id":"https://openalex.org/C92995354","wikidata":"https://www.wikidata.org/wiki/Q5165499","display_name":"Continuous optimization","level":4,"score":0.41825270652770996},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2388293445110321},{"id":"https://openalex.org/C122357587","wikidata":"https://www.wikidata.org/wiki/Q6934508","display_name":"Multi-swarm optimization","level":3,"score":0.22220396995544434},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19671404361724854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1723208725452423},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469801","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469801","pdf_url":null,"source":{"id":"https://openalex.org/S4210221532","display_name":"ACM Transactions on Evolutionary Learning and Optimization","issn_l":"2688-299X","issn":["2688-299X","2688-3007"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Evolutionary Learning and Optimization","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G7372727324","display_name":null,"funder_award_id":"146371743-TRR 89","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1518106236","https://openalex.org/W1647513660","https://openalex.org/W1846834309","https://openalex.org/W1886563687","https://openalex.org/W1983688269","https://openalex.org/W1993377828","https://openalex.org/W2013926956","https://openalex.org/W2015135818","https://openalex.org/W2019579488","https://openalex.org/W2025533349","https://openalex.org/W2033630480","https://openalex.org/W2037662824","https://openalex.org/W2081939577","https://openalex.org/W2098907614","https://openalex.org/W2101657530","https://openalex.org/W2125899728","https://openalex.org/W2133354214","https://openalex.org/W2143381319","https://openalex.org/W2149726897","https://openalex.org/W2156106639","https://openalex.org/W2165170741","https://openalex.org/W2166364496","https://openalex.org/W2182144464","https://openalex.org/W2415757063","https://openalex.org/W2558150887","https://openalex.org/W2883039463","https://openalex.org/W2951774549","https://openalex.org/W4254227598","https://openalex.org/W4300223101","https://openalex.org/W4384024444","https://openalex.org/W6807091881"],"related_works":["https://openalex.org/W3093963944","https://openalex.org/W4318703531","https://openalex.org/W4304194161","https://openalex.org/W4252419006","https://openalex.org/W4226220869","https://openalex.org/W2809500545","https://openalex.org/W4386159657","https://openalex.org/W2140496876","https://openalex.org/W4291270681","https://openalex.org/W3017736765"],"abstract_inverted_index":{"Real-world":[0],"problems":[1,17,146,199],"typically":[2],"require":[3],"the":[4,76,99,105,141,177,203,213,220,232,235],"simultaneous":[5],"optimization":[6,16,40,127,144,158,174,190,198],"of":[7,13,23,78,98,109,145,166,196,207,212,231,234,241],"multiple,":[8],"often":[9],"conflicting":[10],"objectives.":[11,150],"Many":[12],"these":[14],"multi-objective":[15,126,173,189,197],"are":[18,42,184,227],"characterized":[19],"by":[20,54,131,162],"wide":[21],"ranges":[22],"uncertainties":[24,167],"in":[25,107,205,239,247],"their":[26,134],"decision":[27],"variables":[28],"or":[29,61],"objective":[30],"functions.":[31],"To":[32],"cope":[33],"with":[34,50,81,123,147],"such":[35,114],"uncertainties,":[36],"stochastic":[37],"and":[38,95,121,129,181,200,209,244],"robust":[39],"techniques":[41,130,159],"widely":[43],"studied":[44],"aiming":[45],"to":[46,249],"distinguish":[47],"candidate":[48,79],"solutions":[49,80],"uncertain":[51,82,111,149],"objectives":[52,83],"specified":[53],"confidence":[55],"intervals,":[56],"probability":[57,100],"distributions,":[58],"sampled":[59],"data,":[60],"uncertainty":[62,222],"sets.":[63],"In":[64],"this":[65,67],"scope,":[66],"article":[68],"first":[69],"introduces":[70],"a":[71,152,169,194],"novel":[72],"empirical":[73],"approach":[74],"for":[75,155,172],"comparison":[77,90,136,179,215,237,248],"that":[84,101,192],"can":[85,117],"follow":[86],"arbitrary":[87],"distributions.":[88],"The":[89],"is":[91,160,217],"performed":[92],"through":[93],"accurate":[94],"efficient":[96],"calculations":[97],"one":[102],"solution":[103],"dominates":[104],"other":[106],"terms":[108,206,240],"each":[110],"objective.":[112],"Second,":[113],"an":[115,187],"operator":[116,180,216,238],"be":[118],"flexibly":[119],"used":[120],"combined":[122],"many":[124],"existing":[125,188],"frameworks":[128],"just":[132],"substituting":[133],"standard":[135],"operator,":[137],"thus":[138],"easily":[139],"enabling":[140],"Pareto":[142],"front":[143],"multiple":[148],"Third,":[151],"new":[153,178,236],"benchmark":[154,171,182],"evaluating":[156],"uncertainty-aware":[157],"introduced":[161,221],"incorporating":[163],"different":[164],"types":[165],"into":[168,186],"well-known":[170],"problems.":[175],"Fourth,":[176],"suite":[183],"integrated":[185],"framework":[191],"features":[193],"selection":[195],"algorithms.":[201],"Fifth,":[202],"efficiency":[204],"performance":[208],"execution":[210],"time":[211],"proposed":[214,251],"evaluated":[218],"on":[219],"benchmark.":[223],"Finally,":[224],"statistical":[225],"tests":[226],"applied":[228],"giving":[229],"evidence":[230],"superiority":[233],"\\epsilon":[242],"-dominance":[243],"attainment":[245],"surfaces":[246],"previously":[250],"approaches.":[252]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}