{"id":"https://openalex.org/W4416892306","doi":"https://doi.org/10.1016/j.cor.2026.107533","title":"Data-driven interdiction with asymmetric cost uncertainty: A distributionally robust optimization approach","display_name":"Data-driven interdiction with asymmetric cost uncertainty: A distributionally robust optimization approach","publication_year":2026,"publication_date":"2026-05-12","ids":{"openalex":"https://openalex.org/W4416892306","doi":"https://doi.org/10.1016/j.cor.2026.107533"},"language":"en","primary_location":{"id":"doi:10.1016/j.cor.2026.107533","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107533","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"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":"Computers &amp; Operations Research","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.cor.2026.107533","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013736502","display_name":"Sergey S. Ketkov","orcid":"https://orcid.org/0000-0001-9417-6661"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergey S. Ketkov","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9417-6661","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5057562290","display_name":"Oleg A. Prokopyev","orcid":"https://orcid.org/0000-0003-2888-8630"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oleg A. Prokopyev","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2888-8630","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3210,"currency":"USD","value_usd":3210},"apc_paid":{"value":3210,"currency":"USD","value_usd":3210},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00120183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"194","issue":null,"first_page":"107533","last_page":"107533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11807","display_name":"Infrastructure Resilience and Vulnerability Analysis","score":0.7908999919891357,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11807","display_name":"Infrastructure Resilience and Vulnerability Analysis","score":0.7908999919891357,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11413","display_name":"Risk and Portfolio Optimization","score":0.12790000438690186,"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/T13371","display_name":"Military Defense Systems Analysis","score":0.011800000444054604,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/interdiction","display_name":"Interdiction","score":0.9301000237464905},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.8242999911308289},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7110000252723694},{"id":"https://openalex.org/keywords/bilevel-optimization","display_name":"Bilevel optimization","score":0.6292999982833862},{"id":"https://openalex.org/keywords/stochastic-programming","display_name":"Stochastic programming","score":0.6165000200271606},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5044999718666077},{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.4952000081539154},{"id":"https://openalex.org/keywords/complete-information","display_name":"Complete information","score":0.47850000858306885},{"id":"https://openalex.org/keywords/stochastic-optimization","display_name":"Stochastic optimization","score":0.4311000108718872}],"concepts":[{"id":"https://openalex.org/C124119293","wikidata":"https://www.wikidata.org/wiki/Q6046081","display_name":"Interdiction","level":2,"score":0.9301000237464905},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.8242999911308289},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.7373999953269958},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7110000252723694},{"id":"https://openalex.org/C3309286","wikidata":"https://www.wikidata.org/wiki/Q4907693","display_name":"Bilevel optimization","level":3,"score":0.6292999982833862},{"id":"https://openalex.org/C137631369","wikidata":"https://www.wikidata.org/wiki/Q7617831","display_name":"Stochastic programming","level":2,"score":0.6165000200271606},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.4952000081539154},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.47850000858306885},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47749999165534973},{"id":"https://openalex.org/C194387892","wikidata":"https://www.wikidata.org/wiki/Q1747770","display_name":"Stochastic optimization","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.39879998564720154},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.3815999925136566},{"id":"https://openalex.org/C27665512","wikidata":"https://www.wikidata.org/wiki/Q3042795","display_name":"Benders' decomposition","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35830000042915344},{"id":"https://openalex.org/C2777634741","wikidata":"https://www.wikidata.org/wiki/Q768993","display_name":"Wasserstein metric","level":2,"score":0.35760000348091125},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C31531917","wikidata":"https://www.wikidata.org/wiki/Q915157","display_name":"Robust control","level":3,"score":0.3070000112056732},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C115527620","wikidata":"https://www.wikidata.org/wiki/Q769909","display_name":"Nonlinear programming","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C199510392","wikidata":"https://www.wikidata.org/wiki/Q1184602","display_name":"Stackelberg competition","level":2,"score":0.26179999113082886}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1016/j.cor.2026.107533","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107533","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"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":"Computers &amp; Operations Research","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2504.19022","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.19022","pdf_url":"https://arxiv.org/pdf/2504.19022","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:arXiv.org:2504.19022","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2504.19022","pdf_url":"https://arxiv.org/pdf/2504.19022","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.48550/arxiv.2504.19022","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2504.19022","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2504.19022","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":"article"},{"id":"doi:10.5167/uzh-434198","is_oa":true,"landing_page_url":"https://doi.org/10.5167/uzh-434198","pdf_url":null,"source":{"id":"https://openalex.org/S7407051291","display_name":"Universit\u00e4t Z\u00fcrich, ZORA","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"article-journal"}],"best_oa_location":{"id":"doi:10.1016/j.cor.2026.107533","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cor.2026.107533","pdf_url":null,"source":{"id":"https://openalex.org/S173256270","display_name":"Computers & Operations Research","issn_l":"0305-0548","issn":["0305-0548","1873-765X"],"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":"Computers &amp; Operations Research","raw_type":"journal-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":{"We":[0],"consider":[1],"a":[2,15,39,66,95,151,163,168,176,191,196,209],"class":[3,210],"of":[4,118,130,211,215],"stochastic":[5],"interdiction":[6,69,218],"games":[7],"between":[8],"an":[9],"upper-level":[10],"decision-maker":[11,17],"(the":[12,18],"leader)":[13],"and":[14,51,93,161,202,227],"lower-level":[16],"follower),":[19],"where":[20,72,135],"uncertainty":[21,112],"lies":[22],"in":[23,35,103],"the":[24,30,49,52,61,83,108,119,131,136,144,181,186,216,224,228,233],"follower's":[25,31,120,145],"objective":[26],"function":[27],"coefficients.":[28],"Specifically,":[29],"profits":[32],"(or":[33],"costs)":[34],"our":[36,104],"model":[37],"comprise":[38],"random":[40],"vector,":[41],"whose":[42],"probability":[43],"distribution":[44],"is":[45],"estimated":[46],"independently":[47],"by":[48],"leader":[50,109,137],"follower,":[53],"based":[54,81],"on":[55,82],"their":[56],"own":[57],"data.":[58,121,146],"To":[59,184],"address":[60,185],"distributional":[62],"uncertainty,":[63],"we":[64,89,125,189,220],"formulate":[65],"distributionally":[67,77],"robust":[68,78,177],"(DRI)":[70],"model,":[71,88,134],"both":[73],"decision-makers":[74],"solve":[75],"conventional":[76],"optimization":[79,106,178],"problems":[80],"Wasserstein":[84],"metric.":[85],"For":[86],"this":[87,123],"prove":[90],"asymptotic":[91,204],"consistency":[92],"derive":[94],"polynomial-size":[96],"mixed-integer":[97],"linear":[98],"programming":[99],"(MILP)":[100],"reformulation.":[101],"Furthermore,":[102],"bilevel":[105],"context,":[107],"may":[110],"face":[111],"due":[113],"to":[114,157,167],"its":[115],"incomplete":[116,139],"knowledge":[117],"In":[122],"regard,":[124],"propose":[126,190],"two":[127],"distinct":[128],"approximations":[129],"true":[132],"DRI":[133],"has":[138],"or":[140],"no":[141],"information":[142,225],"about":[143],"The":[147,172],"first":[148],"approach":[149,174,179],"employs":[150],"pessimistic":[152],"approximation,":[153],"which":[154],"turns":[155],"out":[156],"be":[158],"computationally":[159],"challenging":[160],"requires":[162],"specialized":[164],"reformulation":[165,201],"amenable":[166],"Benders-type":[169],"decomposition":[170],"algorithm.":[171],"second":[173],"leverages":[175],"from":[180],"leader's":[182],"perspective.":[183],"resulting":[187],"problem,":[188,219],"scenario-based":[192],"approximation":[193],"that":[194],"admits":[195],"potentially":[197],"large":[198],"single-level":[199],"MILP":[200],"satisfies":[203],"robustness":[205],"guarantees.":[206],"Finally,":[207],"for":[208],"randomly":[212],"generated":[213],"instances":[214],"packing":[217],"evaluate":[221],"numerically":[222],"how":[223],"asymmetry":[226],"decision-makers'":[229],"risk":[230],"preferences":[231],"affect":[232],"models'":[234],"out-of-sample":[235],"performance.":[236]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
