{"id":"https://openalex.org/W4403676534","doi":"https://doi.org/10.1109/case59546.2024.10711747","title":"Efficient Job Shop Scheduling via Graph based Deep Reinforcement Learning with Adaptive Multi-Action Selection","display_name":"Efficient Job Shop Scheduling via Graph based Deep Reinforcement Learning with Adaptive Multi-Action Selection","publication_year":2024,"publication_date":"2024-08-28","ids":{"openalex":"https://openalex.org/W4403676534","doi":"https://doi.org/10.1109/case59546.2024.10711747"},"language":"en","primary_location":{"id":"doi:10.1109/case59546.2024.10711747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040396964","display_name":"Jeongwon Park","orcid":"https://orcid.org/0000-0003-4988-302X"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeongwon Park","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020350875","display_name":"Yutong Su","orcid":"https://orcid.org/0009-0007-9319-9977"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yutong Su","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041757568","display_name":"Feng Ju","orcid":"https://orcid.org/0000-0003-3452-0795"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Ju","raw_affiliation_strings":["Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University,School of Computing and Augmented Intelligence,Tempe,AZ,USA,85281","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2949","last_page":"2954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12546","display_name":"Smart Parking Systems Research","score":0.9332000017166138,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12546","display_name":"Smart Parking Systems Research","score":0.9332000017166138,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.7843874096870422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7628901600837708},{"id":"https://openalex.org/keywords/action-selection","display_name":"Action selection","score":0.6662188172340393},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5040653944015503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4884880781173706},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.48589152097702026},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3247984051704407},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.24879825115203857},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08049803972244263},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.059247344732284546},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.058937132358551025}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7843874096870422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628901600837708},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.6662188172340393},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5040653944015503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4884880781173706},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.48589152097702026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3247984051704407},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.24879825115203857},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08049803972244263},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.059247344732284546},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.058937132358551025},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case59546.2024.10711747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.699999988079071}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1967992532","https://openalex.org/W1968822565","https://openalex.org/W1976618788","https://openalex.org/W2016740242","https://openalex.org/W2021040818","https://openalex.org/W2076402732","https://openalex.org/W2104517380","https://openalex.org/W2128882994","https://openalex.org/W2156391157","https://openalex.org/W2258713819","https://openalex.org/W2618749399","https://openalex.org/W3020917412","https://openalex.org/W3128766876","https://openalex.org/W4282946405","https://openalex.org/W4377088856","https://openalex.org/W4383752013","https://openalex.org/W4387123494","https://openalex.org/W4391407255","https://openalex.org/W4393147788","https://openalex.org/W6631190155","https://openalex.org/W6741002519","https://openalex.org/W6754929296","https://openalex.org/W6766978945","https://openalex.org/W6784473743"],"related_works":["https://openalex.org/W3172150420","https://openalex.org/W2107725657","https://openalex.org/W4306904969","https://openalex.org/W2015051472","https://openalex.org/W2168501056","https://openalex.org/W2120009678","https://openalex.org/W3204654320","https://openalex.org/W2037601570","https://openalex.org/W2912947802","https://openalex.org/W2123856982"],"abstract_inverted_index":{"The":[0,114,162,174],"Job":[1],"Shop":[2],"Scheduling":[3],"Problem":[4],"(JSSP)":[5],"is":[6,26,39,89,119],"a":[7,27,54,59,74,80,110],"widely":[8,28],"studied":[9],"combinatorial":[10],"optimization":[11],"challenge":[12],"with":[13,103,157],"significant":[14,190],"real-world":[15],"applications,":[16],"characterized":[17],"by":[18,52,106],"its":[19],"NP-hard":[20],"complexity.":[21],"Priority":[22],"dispatching":[23,160],"rule":[24],"(PDR)":[25],"used":[29,120],"heuristic":[30],"to":[31,49,91,121,126],"solve":[32],"JSSP.":[33],"Unfortunately,":[34],"designing":[35],"an":[36,46,136],"appropriate":[37],"PDR":[38],"time-consuming.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44,134],"present":[45],"efficient":[47],"solution":[48],"the":[50,93,96,107,123,143,146,171,177,184],"JSSP":[51,72,100,151],"introducing":[53],"novel":[55],"framework":[56],"based":[57],"on":[58,149],"weighted":[60,85],"Graph":[61,86],"Isomorphic":[62,87],"Network":[63,88],"and":[64,154],"deep":[65],"reinforcement":[66],"learning.":[67],"Our":[68],"approach":[69,188],"involves":[70],"representing":[71],"through":[73],"disjunctive":[75,97],"graph,":[76],"reformulating":[77],"it":[78,156],"as":[79],"Markov":[81],"decision":[82],"process.":[83],"A":[84],"generated":[90],"learn":[92],"representation":[94],"of":[95,99,112,145,176,186],"graph":[98],"during":[101],"solving,":[102],"weights":[104],"given":[105],"relationship":[108],"between":[109],"pair":[111],"nodes.":[113],"Proximal":[115],"Policy":[116],"Optimization":[117],"(PPO)":[118],"train":[122],"policy":[124],"network":[125],"get":[127],"high-quality":[128],"PDRs.":[129],"To":[130],"enhance":[131],"computational":[132],"efficiency,":[133],"introduce":[135],"adaptive":[137,178],"multi-action":[138,179],"selection":[139,180],"strategy.":[140],"We":[141],"evaluate":[142],"performance":[144],"proposed":[147,168],"method":[148,169],"public":[150],"benchmark":[152],"instances":[153],"compare":[155],"other":[158],"well-known":[159],"rules.":[161],"experiment":[163],"results":[164],"show":[165],"that":[166],"our":[167,187],"achieves":[170],"shortest":[172],"makespan.":[173],"incorporation":[175],"strategy":[181],"further":[182],"enhances":[183],"efficiency":[185],"without":[189],"degradation":[191],"in":[192],"scheduling":[193],"performance.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}