{"id":"https://openalex.org/W7163276776","doi":"https://doi.org/10.1016/j.swevo.2026.102428","title":"Fairness-constrained influence maximisation via multi-objective optimisation","display_name":"Fairness-constrained influence maximisation via multi-objective optimisation","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163276776","doi":"https://doi.org/10.1016/j.swevo.2026.102428"},"language":"en","primary_location":{"id":"doi:10.1016/j.swevo.2026.102428","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.swevo.2026.102428","pdf_url":null,"source":{"id":"https://openalex.org/S2764346689","display_name":"Swarm and Evolutionary Computation","issn_l":"2210-6502","issn":["2210-6502","2210-6510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Swarm and Evolutionary Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.swevo.2026.102428","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137616477","display_name":"Ziying Zhao","orcid":"https://orcid.org/0000-0003-1375-6619"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziying Zhao","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-1375-6619","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137699858","display_name":"Weihua Li","orcid":"https://orcid.org/0000-0001-9215-4979"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weihua Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9215-4979","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137694810","display_name":"Jing Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Ma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137697564","display_name":"Jianhua Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianhua Jiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137710667","display_name":"Quan Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quan Bai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129674985","display_name":"Wen Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen Gu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3700,"currency":"USD","value_usd":3700},"apc_paid":{"value":3700,"currency":"USD","value_usd":3700},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.86429409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"106","issue":null,"first_page":"102428","last_page":"102428"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.09459999948740005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.09459999948740005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11031","display_name":"Game Theory and Applications","score":0.05820000171661377,"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"}},{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.05730000138282776,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.28439998626708984},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.24320000410079956},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.226500004529953},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.20999999344348907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.796999990940094},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3905999958515167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3278000056743622},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.2973000109195709},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24789999425411224},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.24320000410079956},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.226500004529953},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.20999999344348907},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.1979999989271164}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.swevo.2026.102428","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.swevo.2026.102428","pdf_url":null,"source":{"id":"https://openalex.org/S2764346689","display_name":"Swarm and Evolutionary Computation","issn_l":"2210-6502","issn":["2210-6502","2210-6510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Swarm and Evolutionary Computation","raw_type":"journal-article"},{"id":"pmh:oai:openrepository.aut.ac.nz:10292/21324","is_oa":true,"landing_page_url":"http://hdl.handle.net/10292/21324","pdf_url":null,"source":{"id":"https://openalex.org/S4306401809","display_name":"Tuwhera (Auckland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39854758","host_organization_name":"Auckland University of Technology","host_organization_lineage":["https://openalex.org/I39854758"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1016/j.swevo.2026.102428","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.swevo.2026.102428","pdf_url":null,"source":{"id":"https://openalex.org/S2764346689","display_name":"Swarm and Evolutionary Computation","issn_l":"2210-6502","issn":["2210-6502","2210-6510"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Swarm and Evolutionary Computation","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.437479168176651,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W68645389","https://openalex.org/W1846834309","https://openalex.org/W1971937094","https://openalex.org/W2053900989","https://openalex.org/W2056944867","https://openalex.org/W2061820396","https://openalex.org/W2073415627","https://openalex.org/W2094234423","https://openalex.org/W2108614537","https://openalex.org/W2108968575","https://openalex.org/W2123808725","https://openalex.org/W2126105956","https://openalex.org/W2141403143","https://openalex.org/W2142517301","https://openalex.org/W2143381319","https://openalex.org/W2146950091","https://openalex.org/W2165171393","https://openalex.org/W2174096823","https://openalex.org/W2294347342","https://openalex.org/W2464384554","https://openalex.org/W2624035516","https://openalex.org/W2743418339","https://openalex.org/W2770118518","https://openalex.org/W2793837878","https://openalex.org/W2848126713","https://openalex.org/W2897249806","https://openalex.org/W2907999153","https://openalex.org/W2914307045","https://openalex.org/W2946235107","https://openalex.org/W2961534768","https://openalex.org/W2965173882","https://openalex.org/W2987373818","https://openalex.org/W3006978394","https://openalex.org/W3022163979","https://openalex.org/W3034616536","https://openalex.org/W3134837995","https://openalex.org/W4205531740","https://openalex.org/W4282559224","https://openalex.org/W4289866591","https://openalex.org/W4292387417","https://openalex.org/W4307724673","https://openalex.org/W4388040942","https://openalex.org/W4405754299"],"related_works":[],"abstract_inverted_index":{"The":[0],"Influence":[1,56],"Maximisation":[2,57],"(IM)":[3],"problem":[4],"seeks":[5],"to":[6,13,136,163],"select":[7],"a":[8,18,85,119,158,182,211],"set":[9],"of":[10,45,107],"seed":[11,141],"nodes":[12],"maximise":[14],"information":[15],"diffusion":[16,230],"in":[17,27,39,191,231],"network.":[19],"While":[20],"existing":[21],"approaches":[22],"have":[23],"achieved":[24],"significant":[25],"improvements":[26],"overall":[28],"diffusion,":[29],"they":[30],"often":[31],"overlook":[32],"fairness":[33,102,145,151],"across":[34,110],"communities,":[35],"which":[36,60],"can":[37],"result":[38],"biased":[40],"dissemination":[41],"and":[42,65,84,150,180,215,226,239],"the":[43,53,73,77,80,97,105,131,148,203],"exclusion":[44],"disadvantaged":[46],"groups.":[47],"To":[48,112],"address":[49],"this,":[50],"we":[51],"define":[52],"Fair":[54],"Multi-objective":[55],"(FMOIM)":[58],"problem,":[59],"jointly":[61],"optimises":[62],"influence":[63,127],"spread":[64,149],"equity":[66],"fairness.":[67],"Equity":[68],"Fairness":[69],"is":[70,116],"modelled":[71],"at":[72],"community":[74],"level":[75],"as":[76,118,234],"alignment":[78],"between":[79],"realised":[81],"diffusion-benefit":[82],"distribution":[83],"desired":[86],"reference":[87,98],"allocation.":[88,241],"Jensen\u2013Shannon":[89],"divergence":[90],"(JSD)":[91],"similarity":[92],"quantifies":[93],"distributional":[94],"deviation":[95],"from":[96],"allocation,":[99],"while":[100,176],"Jain\u2019s":[101],"index":[103],"characterises":[104],"evenness":[106],"benefit":[108],"allocation":[109],"communities.":[111],"solve":[113],"FMOIM,":[114],"FairWolf":[115,153,204],"proposed":[117],"problem-driven":[120],"discrete":[121,159],"multi-objective":[122,193],"optimisation":[123],"model":[124,205],"for":[125,228],"fairness-aware":[126,229],"maximisation.":[128],"It":[129],"reformulates":[130],"Grey":[132],"Wolf":[133],"Optimiser":[134],"dynamics":[135],"search":[137,194],"directly":[138],"over":[139],"fixed-budget":[140],"sets":[142],"under":[143],"community-level":[144],"objectives,":[146],"capturing":[147],"trade-off.":[152],"incorporates":[154],"three":[155],"components:":[156],"(i)":[157],"position-updating":[160],"mechanism":[161,186],"tailored":[162],"seed-set":[164],"construction,":[165],"(ii)":[166],"an":[167],"Explorer-Augmented":[168],"Leader":[169],"Selection":[170],"strategy":[171],"that":[172,187,202],"enhances":[173],"population":[174],"diversity":[175],"maintaining":[177],"convergence":[178],"pressure,":[179],"(iii)":[181],"Hypervolume":[183],"(HV)-triggered":[184],"perturbation":[185],"adaptively":[188],"mitigates":[189],"stagnation":[190],"non-convex":[192],"spaces.":[195],"Experiments":[196],"on":[197],"eight":[198],"real-world":[199],"networks":[200],"demonstrate":[201,223],"consistently":[206],"outperforms":[207],"state-of-the-art":[208],"baselines,":[209],"yielding":[210],"higher":[212],"HV":[213],"value":[214],"more":[216],"uniformly":[217],"distributed":[218],"Pareto":[219],"fronts.":[220],"These":[221],"results":[222],"its":[224],"effectiveness":[225],"practicality":[227],"applications":[232],"such":[233],"viral":[235],"marketing,":[236],"public":[237],"health,":[238],"resource":[240]},"counts_by_year":[],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2026-06-03T00:00:00"}