{"id":"https://openalex.org/W4414229496","doi":"https://doi.org/10.1109/access.2025.3610615","title":"Hierarchical Deep Reinforcement Learning for Multi-Objective Integrated Circuit Physical Layout Optimization With Congestion-Aware Reward Shaping","display_name":"Hierarchical Deep Reinforcement Learning for Multi-Objective Integrated Circuit Physical Layout Optimization With Congestion-Aware Reward Shaping","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414229496","doi":"https://doi.org/10.1109/access.2025.3610615"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3610615","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3610615","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3610615","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003692319","display_name":"Haijian Zhang","orcid":"https://orcid.org/0000-0001-8314-6563"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haijian Zhang","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101940769","display_name":"Yao Ge","orcid":"https://orcid.org/0000-0001-6314-3891"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao Ge","raw_affiliation_strings":["University of Miami, Coral Gables, FL, USA","University of Miami, Coral Gables, USA"],"affiliations":[{"raw_affiliation_string":"University of Miami, Coral Gables, FL, USA","institution_ids":["https://openalex.org/I145608581"]},{"raw_affiliation_string":"University of Miami, Coral Gables, USA","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044473770","display_name":"Xiuyuan Zhao","orcid":"https://orcid.org/0009-0003-9938-0292"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiuyuan Zhao","raw_affiliation_strings":["Stevens Institute of Technology, Hoboken, NJ, USA","Stevens Institute of Technology, Hoboken, USA"],"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]},{"raw_affiliation_string":"Stevens Institute of Technology, Hoboken, USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070177593","display_name":"Jiyuan Wang","orcid":"https://orcid.org/0009-0009-7957-777X"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiyuan Wang","raw_affiliation_strings":["Duke University, Durham, NC, USA","Duke University, Durham, USA"],"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Duke University, Durham, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003692319"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.1186,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95692149,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"162533","last_page":"162551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11527","display_name":"3D IC and TSV technologies","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9688000082969666,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8219000101089478},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.5335000157356262},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4959999918937683},{"id":"https://openalex.org/keywords/physical-design","display_name":"Physical design","score":0.4934999942779541},{"id":"https://openalex.org/keywords/electronic-design-automation","display_name":"Electronic design automation","score":0.45890000462532043},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4081999957561493},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.3546000123023987}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8219000101089478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7950999736785889},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.5335000157356262},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C188817802","wikidata":"https://www.wikidata.org/wiki/Q13426855","display_name":"Physical design","level":3,"score":0.4934999942779541},{"id":"https://openalex.org/C64260653","wikidata":"https://www.wikidata.org/wiki/Q1194864","display_name":"Electronic design automation","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.40299999713897705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3666999936103821},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.34709998965263367},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.34130001068115234},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32820001244544983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3255999982357025},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C14580979","wikidata":"https://www.wikidata.org/wiki/Q876049","display_name":"Very-large-scale integration","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C2778588580","wikidata":"https://www.wikidata.org/wiki/Q6043060","display_name":"Integrated design","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3610615","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3610615","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3d998c4a397e4768a4797d1a95c89e37","is_oa":true,"landing_page_url":"https://doaj.org/article/3d998c4a397e4768a4797d1a95c89e37","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 162533-162551 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3610615","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3610615","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1983991003","https://openalex.org/W2052533471","https://openalex.org/W2119814947","https://openalex.org/W2128252711","https://openalex.org/W2150206948","https://openalex.org/W2550536042","https://openalex.org/W2945706499","https://openalex.org/W2992137891","https://openalex.org/W2996886069","https://openalex.org/W3040707741","https://openalex.org/W3040947815","https://openalex.org/W3168892396","https://openalex.org/W3169517138","https://openalex.org/W3171752851","https://openalex.org/W3200354549","https://openalex.org/W4200256413","https://openalex.org/W4251390903","https://openalex.org/W4282821489","https://openalex.org/W4287891166","https://openalex.org/W4291653578","https://openalex.org/W4308308546","https://openalex.org/W4312729670","https://openalex.org/W4313306336","https://openalex.org/W4313890168","https://openalex.org/W4391612219","https://openalex.org/W4392680688","https://openalex.org/W4392681172","https://openalex.org/W4396949831","https://openalex.org/W4399996962","https://openalex.org/W4401415454","https://openalex.org/W4404565059","https://openalex.org/W4408151607","https://openalex.org/W4410716429"],"related_works":[],"abstract_inverted_index":{"Physical":[0],"layout":[1,55],"optimization":[2,56,114],"in":[3,159,164,170,227],"integrated":[4],"circuit":[5],"(IC)":[6],"design":[7,22,65,127,229],"remains":[8],"a":[9,44,70,86,93,97,105,131],"critical":[10],"challenge":[11],"as":[12],"semiconductor":[13],"technology":[14],"scales":[15],"toward":[16],"advanced":[17],"nodes,":[18],"where":[19,96],"traditional":[20],"electronic":[21],"automation":[23],"(EDA)":[24],"tools":[25,177],"struggle":[26],"to":[27,174],"simultaneously":[28],"optimize":[29],"multiple":[30],"conflicting":[31],"objectives":[32],"including":[33],"routing":[34,143,160],"congestion,":[35,161],"power":[36,165],"consumption,":[37],"and":[38,79,104,129,141,167,178,216],"timing":[39,171],"performance.":[40],"This":[41],"paper":[42],"presents":[43],"novel":[45,132],"hierarchical":[46,87,210],"deep":[47,193],"reinforcement":[48,194],"learning":[49,195],"(HDRL)":[50],"framework":[51,91,183,219],"for":[52],"multi-objective":[53],"IC":[54],"that":[57,75,135,151,220],"addresses":[58],"the":[59,209,222],"exponential":[60],"complexity":[61],"of":[62,224],"modern":[63],"chip":[64],"spaces.":[66],"Our":[67,206],"approach":[68],"introduces":[69],"congestion-aware":[71,213],"reward":[72,214],"shaping":[73],"mechanism":[74,204],"dynamically":[76],"balances":[77],"exploration":[78],"exploitation":[80],"while":[81,197],"incorporating":[82],"domain-specific":[83],"knowledge":[84],"through":[85,202],"policy":[88,99,107,211],"decomposition.":[89],"The":[90,182],"employs":[92],"dual-level":[94],"architecture":[95],"high-level":[98],"manages":[100],"global":[101,142],"placement":[102,110,200],"strategies":[103],"low-level":[106],"handles":[108],"detailed":[109],"refinements,":[111],"enabling":[112],"efficient":[113],"across":[115],"different":[116],"granularities.":[117],"We":[118],"integrate":[119],"adaptive":[120],"action":[121],"space":[122],"pruning":[123],"based":[124],"on":[125,147],"physical":[126,228],"rules":[128],"propose":[130],"state":[133],"representation":[134],"captures":[136],"both":[137],"local":[138],"congestion":[139],"patterns":[140],"accessibility.":[144],"Extensive":[145],"experiments":[146],"OpenROAD":[148],"benchmarks":[149],"demonstrate":[150],"our":[152],"method":[153],"achieves":[154],"an":[155],"average":[156],"23.7%":[157],"reduction":[158],"18.4%":[162],"improvement":[163],"efficiency,":[166],"15.2%":[168],"enhancement":[169],"closure":[172],"compared":[173],"state-of-the-art":[175],"commercial":[176],"recent":[179],"learning-based":[180],"approaches.":[181],"maintains":[184],"computational":[185],"efficiency":[186],"with":[187],"40%":[188],"faster":[189],"convergence":[190],"than":[191],"baseline":[192],"methods":[196],"providing":[198],"interpretable":[199],"decisions":[201],"attention":[203],"visualization.":[205],"contributions":[207],"include":[208],"architecture,":[212],"formulation,":[215],"comprehensive":[217],"evaluation":[218],"advances":[221],"integration":[223],"artificial":[225],"intelligence":[226],"automation.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}