{"id":"https://openalex.org/W4415420631","doi":"https://doi.org/10.1007/s10732-025-09572-3","title":"Exploiting user-supplied Decompositions inside Heuristics","display_name":"Exploiting user-supplied Decompositions inside Heuristics","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4415420631","doi":"https://doi.org/10.1007/s10732-025-09572-3"},"language":"en","primary_location":{"id":"doi:10.1007/s10732-025-09572-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10732-025-09572-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10732-025-09572-3.pdf","source":{"id":"https://openalex.org/S111418578","display_name":"Journal of Heuristics","issn_l":"1381-1231","issn":["1381-1231","1572-9397"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Heuristics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10732-025-09572-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029595036","display_name":"Katrin Halbig","orcid":"https://orcid.org/0000-0002-8730-3447"},"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":"Katrin Halbig","raw_affiliation_strings":["Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr.\u00a011, 91058, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-8730-3447","affiliations":[{"raw_affiliation_string":"Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr.\u00a011, 91058, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094196869","display_name":"Adrian G\u00f6\u00df","orcid":"https://orcid.org/0009-0002-7144-8657"},"institutions":[{"id":"https://openalex.org/I3130238102","display_name":"Lutheran University of Applied Sciences Nuremberg","ror":"https://ror.org/01tbgce33","country_code":"DE","type":"education","lineage":["https://openalex.org/I3130238102"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Adrian G\u00f6\u00df","raw_affiliation_strings":["Analytics & Optimization Lab, University of Technology Nuremberg (UTN), Ulmenstr. 52i, 90443, Nuremberg, Germany","Analytics & Optimization Lab, University of Technology Nuremberg (UTN), Ulmenstr.\u00a052i, 90443, Nuremberg, Germany"],"raw_orcid":"https://orcid.org/0009-0002-7144-8657","affiliations":[{"raw_affiliation_string":"Analytics & Optimization Lab, University of Technology Nuremberg (UTN), Ulmenstr. 52i, 90443, Nuremberg, Germany","institution_ids":["https://openalex.org/I3130238102"]},{"raw_affiliation_string":"Analytics & Optimization Lab, University of Technology Nuremberg (UTN), Ulmenstr.\u00a052i, 90443, Nuremberg, Germany","institution_ids":["https://openalex.org/I3130238102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004374641","display_name":"Dieter Weninger","orcid":"https://orcid.org/0000-0002-1333-8591"},"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":"Dieter Weninger","raw_affiliation_strings":["Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","Department of Mathematics, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr.\u00a011, 91058, Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-1333-8591","affiliations":[{"raw_affiliation_string":"Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department of Mathematics, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr. 11, 91058, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department of Data Science, Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Cauerstr.\u00a011, 91058, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5029595036"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31928007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9984999895095825,"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/T10142","display_name":"Formal Methods in Verification","score":0.9980000257492065,"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/T11106","display_name":"Data Management and Algorithms","score":0.9958999752998352,"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/heuristics","display_name":"Heuristics","score":0.84170001745224},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.6929000020027161},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5785999894142151},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.558899998664856},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4887999892234802},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4652999937534332},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.3804999887943268}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.84170001745224},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.6929000020027161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6430000066757202},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5785999894142151},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.558899998664856},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5332000255584717},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4887999892234802},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29580000042915344},{"id":"https://openalex.org/C2778258933","wikidata":"https://www.wikidata.org/wiki/Q16918986","display_name":"Decomposition method (queueing theory)","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.25949999690055847},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25049999356269836}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s10732-025-09572-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10732-025-09572-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10732-025-09572-3.pdf","source":{"id":"https://openalex.org/S111418578","display_name":"Journal of Heuristics","issn_l":"1381-1231","issn":["1381-1231","1572-9397"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Heuristics","raw_type":"journal-article"},{"id":"pmh:oai:open.fau.de:openfau/37615","is_oa":true,"landing_page_url":"https://open.fau.de/handle/openfau/37615","pdf_url":"https://open.fau.de/bitstreams/8db85337-c33d-49c8-ade6-edc5c4f839b6/download","source":{"id":"https://openalex.org/S7407055110","display_name":"OPUS FAU - Online publication system of Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:econstor.eu:10419/330213","is_oa":true,"landing_page_url":"https://hdl.handle.net/10419/330213","pdf_url":null,"source":{"id":"https://openalex.org/S4306401696","display_name":"Econstor (Econstor)","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doc-type:article"}],"best_oa_location":{"id":"doi:10.1007/s10732-025-09572-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10732-025-09572-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10732-025-09572-3.pdf","source":{"id":"https://openalex.org/S111418578","display_name":"Journal of Heuristics","issn_l":"1381-1231","issn":["1381-1231","1572-9397"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Heuristics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320873","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415420631.pdf","grobid_xml":"https://content.openalex.org/works/W4415420631.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1504925519","https://openalex.org/W1534309112","https://openalex.org/W1989023497","https://openalex.org/W1994556169","https://openalex.org/W2002723731","https://openalex.org/W2008454042","https://openalex.org/W2044121814","https://openalex.org/W2045734922","https://openalex.org/W2056121010","https://openalex.org/W2080336407","https://openalex.org/W2092997351","https://openalex.org/W2097192020","https://openalex.org/W2103880351","https://openalex.org/W2105560970","https://openalex.org/W2109220922","https://openalex.org/W2125506391","https://openalex.org/W2301790113","https://openalex.org/W2587095554","https://openalex.org/W2624633283","https://openalex.org/W2740548164","https://openalex.org/W2963139252","https://openalex.org/W2990050240","https://openalex.org/W3009834077","https://openalex.org/W3081419633","https://openalex.org/W3085454911","https://openalex.org/W4210791087","https://openalex.org/W4241768805","https://openalex.org/W4242130683","https://openalex.org/W4244863679","https://openalex.org/W4292363360","https://openalex.org/W4313163409","https://openalex.org/W4323261900","https://openalex.org/W4323864042"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Numerous":[1],"industrial":[2],"fields,":[3],"like":[4],"supply":[5],"chain":[6],"management,":[7],"face":[8],"mixed-integer":[9,183],"optimization":[10,184],"problems":[11,17,48],"on":[12,54,107],"a":[13,20,58,67,82,131,136,158],"regular":[14],"basis.":[15],"Such":[16],"typically":[18],"show":[19],"sparse":[21],"structure":[22],"and":[23,102,134],"vary":[24],"in":[25,32,81,130,148,157],"size,":[26],"as":[27,29],"well":[28],"complexity.":[30],"However,":[31],"order":[33],"to":[34,41,45,89,98,140],"satisfy":[35],"customer":[36],"demands,":[37],"it":[38],"is":[39,75],"crucial":[40],"find":[42],"good":[43],"solutions":[44],"all":[46],"such":[47],"quickly.":[49],"Current":[50],"research":[51],"often":[52],"focuses":[53],"the":[55,90,108,117,123,149,179],"development":[56],"of":[57,110,182],"tailored":[59],"approach":[60],"for":[61],"one":[62],"specific":[63],"problem":[64],"class":[65],"with":[66,84],"common":[68],"structure.":[69],"Information":[70],"supplied":[71],"by":[72],"everyday":[73],"users":[74],"usually":[76],"overlooked,":[77],"but":[78],"may":[79],"result":[80],"decomposition":[83,100,175],"weakly":[85],"connected":[86],"blocks":[87],"due":[88],"structural":[91],"sparsity.":[92],"Hence,":[93],"we":[94,114],"present":[95],"three":[96,163],"heuristics":[97,145],"exploit":[99],"information":[101,176],"analyze":[103],"their":[104,155],"value":[105],"based":[106],"type":[109],"decomposition.":[111],"In":[112],"particular,":[113],"newly":[115],"introduce":[116],"heuristic":[118],"Dynamic":[119],"Partition":[120],"Search,":[121],"enhance":[122],"Penalty":[124],"Alternating":[125],"Direction":[126],"Method":[127],"published":[128],"earlier":[129],"basic":[132],"form,":[133],"extend":[135],"framework":[137],"from":[138],"literature":[139],"Decomposition":[141],"Kernel":[142],"Search.":[143],"All":[144],"are":[146],"implemented":[147],"non-commercial":[150],"solver":[151],"SCIP.":[152],"We":[153],"examine":[154],"performance":[156],"comprehensive":[159],"computational":[160,168],"study":[161],"across":[162],"different":[164],"test":[165],"sets.":[166],"The":[167],"results":[169],"indicate":[170],"that":[171],"knowledge":[172],"about":[173],"relevant":[174],"can":[177],"boost":[178],"solution":[180],"process":[181],"problems.":[185]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-24T00:00:00"}
