{"id":"https://openalex.org/W7168132719","doi":"https://doi.org/10.4230/lipics.cp.2026.59","title":"Lightweight Look-Ahead-Based Value Heuristics for Constraint Optimization Problems","display_name":"Lightweight Look-Ahead-Based Value Heuristics for Constraint Optimization Problems","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7168132719","doi":"https://doi.org/10.4230/lipics.cp.2026.59"},"language":"en","primary_location":{"id":"pmh:doi:10.4230/lipics.cp.2026.59","is_oa":true,"landing_page_url":"https://github.com/lihb905/abla","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"type":"conference-paper","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://github.com/lihb905/abla","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086329815","display_name":"Ziyang Yu","orcid":"https://orcid.org/0009-0001-6629-5775"},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu, Ziyang","raw_affiliation_strings":["School of Information Science and Technology, Northeast Normal University, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0004-2136-0926","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northeast Normal University, Changchun, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038076794","display_name":"Hongbo Li","orcid":"https://orcid.org/0000-0002-2664-4117"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Hongbo","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Shanghai University of Finance and Economics, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2664-4117","affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Shanghai University of Finance and Economics, Shanghai, China","institution_ids":["https://openalex.org/I181679659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7483000159263611},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6184999942779541},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5713000297546387},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5544000267982483},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5493000149726868},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4945000112056732},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4771000146865845}],"concepts":[{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7483000159263611},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6984000205993652},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6184999942779541},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6067000031471252},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5713000297546387},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5544000267982483},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5493000149726868},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4945000112056732},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C2776435737","wikidata":"https://www.wikidata.org/wiki/Q7915703","display_name":"Variable neighborhood search","level":3,"score":0.3765000104904175},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2856000065803528},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2847000062465668},{"id":"https://openalex.org/C176783269","wikidata":"https://www.wikidata.org/wiki/Q5164378","display_name":"Constraint logic programming","level":4,"score":0.2761000096797943},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.25699999928474426}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:doi:10.4230/lipics.cp.2026.59","is_oa":true,"landing_page_url":"https://github.com/lihb905/abla","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},{"id":"pmh:oai:drops-oai.dagstuhl.de:26692","is_oa":true,"landing_page_url":"https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.59","pdf_url":null,"source":{"id":"https://openalex.org/S4377196569","display_name":"DROPS (Schloss Dagstuhl \u2013 Leibniz Center for Informatics)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2799853480","host_organization_name":"Schloss Dagstuhl \u2013 Leibniz Center for Informatics","host_organization_lineage":["https://openalex.org/I2799853480"],"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":"InProceedings"},{"id":"doi:10.4230/lipics.cp.2026.59","is_oa":true,"landing_page_url":"https://doi.org/10.4230/lipics.cp.2026.59","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"ConferencePaper"}],"best_oa_location":{"id":"pmh:doi:10.4230/lipics.cp.2026.59","is_oa":true,"landing_page_url":"https://github.com/lihb905/abla","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8574359920","display_name":null,"funder_award_id":"62276060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Bound-Impact":[1],"Value":[2],"Selector":[3],"(BIVS)":[4],"employs":[5],"a":[6,66,70,102],"look-ahead":[7,94,108,128],"strategy":[8,68],"to":[9,17,78,125],"enable":[10],"black-box":[11],"Constraint":[12],"Optimization":[13],"Problem":[14],"(COP)":[15],"solvers":[16],"find":[18],"high-quality":[19],"solutions":[20],"earlier.":[21],"However,":[22],"its":[23,27],"computational":[24],"cost":[25],"prohibits":[26],"use":[28],"throughout":[29],"the":[30,38,45,48,52,56,80,93,99,107,144,155,160],"entire":[31],"search":[32],"process.":[33],"To":[34],"mitigate":[35],"this":[36,62,110],"cost,":[37],"Restricted":[39],"Fixpoint":[40],"(RF)":[41],"approach":[42],"considers":[43],"only":[44,105],"constraints":[46],"on":[47,114],"shortest":[49],"paths":[50],"between":[51,98],"selected":[53],"variable":[54],"and":[55,104,149,159],"objective,":[57],"yielding":[58],"better":[59],"performance.":[60],"In":[61],"paper,":[63],"we":[64],"propose":[65],"lightweight":[67],"from":[69,117],"different":[71],"perspective,":[72],"named":[73],"Assess":[74],"Before":[75],"Look-Ahead":[76],"(ABLA),":[77],"enhance":[79],"performance":[81,145],"of":[82,101,137,146],"look-ahead-based":[83],"value":[84,157,162],"heuristics":[85],"for":[86],"solving":[87],"COPs.":[88],"ABLA":[89,141],"first":[90],"assesses":[91],"whether":[92],"process":[95],"can":[96],"differentiate":[97],"values":[100],"variable,":[103],"performs":[106],"when":[109],"assessment":[111],"passes.":[112],"Experiments":[113],"benchmark":[115],"instances":[116],"recent":[118],"MiniZinc":[119],"Challenges":[120],"demonstrate":[121],"that":[122],"ABLA\u2019s":[123],"decisions":[124],"skip":[126],"redundant":[127],"processes":[129],"are":[130],"highly":[131],"reliable,":[132],"with":[133],"an":[134],"average":[135],"accuracy":[136],"over":[138],"94%.":[139],"Consequently,":[140],"significantly":[142],"boosts":[143],"both":[147],"BIVS":[148],"RF,":[150],"outperforming":[151],"two":[152],"other":[153],"baselines:":[154],"minimum":[156],"heuristic":[158],"RLARF":[161],"heuristic.":[163]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-14T00:00:00"}