{"id":"https://openalex.org/W4282014764","doi":"https://doi.org/10.7315/cde.2022.098","title":"Development of Quay Scheduling Algorithm Based on Reinforcement Learning","display_name":"Development of Quay Scheduling Algorithm Based on Reinforcement Learning","publication_year":2022,"publication_date":"2022-06-09","ids":{"openalex":"https://openalex.org/W4282014764","doi":"https://doi.org/10.7315/cde.2022.098"},"language":"en","primary_location":{"id":"doi:10.7315/cde.2022.098","doi":"https://doi.org/10.7315/cde.2022.098","is_oa":false,"landing_page_url":"https://doi.org/10.7315/cde.2022.098","pdf_url":null,"source":{"id":"https://openalex.org/S2764661988","display_name":"Korean Journal of Computational Design and Engineering","issn_l":"1226-0606","issn":["1226-0606","2288-6036","2508-4003","2508-402X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Korean Journal of Computational Design and Engineering","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5088686112","display_name":"Young-in Cho","orcid":"https://orcid.org/0000-0002-1614-5226","observed_orcids":["https://orcid.org/0000-0002-1614-5226"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Young-In Cho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112529546","display_name":"Seung-Heon Oh","orcid":"https://orcid.org/0009-0009-7656-6522","observed_orcids":["https://orcid.org/0009-0009-7656-6522"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seung-Heon Oh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Dong-Hoon Kwak","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong-Hoon Kwak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047485939","display_name":"Jaeho Choi","orcid":"https://orcid.org/0000-0002-7701-3470","observed_orcids":["https://orcid.org/0000-0002-7701-3470"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jae-Ho Choi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5113774156","display_name":"Jong-Hun Woo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jong-Hun Woo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2837,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.50695051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"27","issue":"2","first_page":"98","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11223","display_name":"Maritime Ports and Logistics","score":0.7515000104904175,"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"}},"topics":[{"id":"https://openalex.org/T11223","display_name":"Maritime Ports and Logistics","score":0.7515000104904175,"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"}},{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.21570000052452087,"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"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.006399999838322401,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/ship-outfitting","display_name":"ship outfitting","score":0.8029999732971191},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.8500000238418579},{"id":"https://openalex.org/keywords/deep-recurrent-q-network","display_name":"deep recurrent Q-network","score":0.847000002861023},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.9879999756813049},{"id":"https://openalex.org/keywords/discrete-event-simulation","display_name":"discrete event simulation","score":0.9599999785423279},{"id":"https://openalex.org/keywords/ship-motion","display_name":"ship motion","score":0.8069999814033508},{"id":"https://openalex.org/keywords/shipbuilding","display_name":"shipbuilding","score":0.5360000133514404}],"concepts":[{"id":"https://openalex.org/C86154893","wikidata":"https://www.wikidata.org/wiki/Q190928","display_name":"Shipyard","level":3,"score":0.8600203990936279},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6472292542457581},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.5742847323417664},{"id":"https://openalex.org/C65542768","wikidata":"https://www.wikidata.org/wiki/Q474200","display_name":"Shipbuilding","level":2,"score":0.5596188902854919},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5481893420219421},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5206234455108643},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.47175130248069763},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.4302263855934143},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4262649416923523},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.424133837223053},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35043442249298096},{"id":"https://openalex.org/C199104240","wikidata":"https://www.wikidata.org/wiki/Q118291","display_name":"Marine engineering","level":1,"score":0.3328675925731659},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.31044524908065796},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.2603391408920288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2458537518978119},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.18986734747886658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09703883528709412},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.7315/cde.2022.098","doi":"https://doi.org/10.7315/cde.2022.098","is_oa":false,"landing_page_url":"https://doi.org/10.7315/cde.2022.098","pdf_url":null,"source":{"id":"https://openalex.org/S2764661988","display_name":"Korean Journal of Computational Design and Engineering","issn_l":"1226-0606","issn":["1226-0606","2288-6036","2508-4003","2508-402X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Korean Journal of Computational Design and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4395673530","https://openalex.org/W1989764070","https://openalex.org/W4413979118","https://openalex.org/W2366011801","https://openalex.org/W4406547278","https://openalex.org/W4409165298","https://openalex.org/W4303645105","https://openalex.org/W4280494418","https://openalex.org/W1952284345","https://openalex.org/W2375189985"],"abstract_inverted_index":{"In":[0,35,96,128],"the":[1,14,27,37,41,46,49,52,68,77,99,113,131,135,148,156,176,188],"shipbuilding,":[2],"outfitting":[3,53],"processes":[4,54],"are":[5,33,55],"mainly":[6],"performed":[7],"on":[8,45,147],"ships":[9,64,83],"moored":[10],"by":[11,105,119,161,180],"quays":[12,29,50,69],"of":[13,40,48,82,92,184,190],"shipyard.":[15],"Quays":[16],"in":[17,73,182],"shipyards":[18],"have":[19],"different":[20],"lengths,":[21],"depths,":[22],"and":[23,94,167,193],"facilities":[24],"so":[25],"that":[26],"allowable":[28],"for":[30,63,134],"each":[31],"ship":[32,191],"limited.":[34],"addition,":[36],"working":[38,78],"efficiency":[39],"quay":[42,100,136],"process":[43,151],"depends":[44],"kinds":[47],"where":[51],"performed.":[56],"As":[57],"a":[58,90,142],"result,":[59],"it":[60,88],"is":[61,89,102,139,159],"inevitable":[62],"to":[65,70],"move":[66],"around":[67],"avoid":[71],"delay":[72],"schedule":[74],"while":[75],"maximizing":[76],"efficiency.":[79],"The":[80,172],"movements":[81],"should":[84],"be":[85,117],"minimized":[86],"because":[87],"waste":[91],"cost":[93],"time.":[95],"most":[97],"shipyards,":[98],"allocation":[101,137],"manually":[103],"determined":[104],"planners":[106],"using":[107,141,153],"their":[108],"own":[109],"implicit":[110],"rules.":[111],"However,":[112],"optimal":[114],"plan":[115],"can\u2019t":[116],"obtained":[118],"those":[120],"heuristics":[121],"which":[122],"only":[123],"considers":[124],"limited":[125],"problem":[126,138],"space.":[127],"this":[129],"study,":[130],"scheduling":[132,157],"algorithm":[133,166,174],"developed":[140],"reinforcement":[143],"learning":[144],"approach.":[145],"Based":[146],"Markov":[149],"decision":[150],"model":[152],"discrete-event":[154],"simulation,":[155],"agent":[158],"trained":[160],"DRQN":[162],"(Deep":[163],"Recurrent":[164],"Q-network)":[165],"tested":[168],"with":[169],"10":[170],"scenarios.":[171],"proposed":[173],"outperforms":[175],"reference":[177],"value":[178],"set":[179],"heuristic":[181],"terms":[183],"three":[185],"KPIs-unallocated":[186],"duration,":[187],"number":[189],"movements,":[192],"ship-quay":[194],"priority":[195],"ratio.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-09-29T14:09:16.559479","created_date":"2022-06-13T00:00:00"}