{"id":"https://openalex.org/W4410153075","doi":"https://doi.org/10.1109/access.2025.3567823","title":"Nearest-Better Clustering-Based Memetic Algorithm for Berth Allocation and Crane Assignment Problem","display_name":"Nearest-Better Clustering-Based Memetic Algorithm for Berth Allocation and Crane Assignment Problem","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410153075","doi":"https://doi.org/10.1109/access.2025.3567823"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3567823","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3567823","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.2025.3567823","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101251254","display_name":"Jiawei Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiawei Wu","raw_affiliation_strings":["School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0005-8795-2913","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101251254"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.5554,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.8334139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"82247","last_page":"82260"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9765999913215637,"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9765999913215637,"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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9605000019073486,"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/memetic-algorithm","display_name":"Memetic algorithm","score":0.8091974854469299},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7293225526809692},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6757700443267822},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.48902472853660583},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.43567174673080444},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38419461250305176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3670429587364197},{"id":"https://openalex.org/keywords/local-search","display_name":"Local search (optimization)","score":0.31433454155921936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17200961709022522}],"concepts":[{"id":"https://openalex.org/C35129592","wikidata":"https://www.wikidata.org/wiki/Q324793","display_name":"Memetic algorithm","level":3,"score":0.8091974854469299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7293225526809692},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6757700443267822},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48902472853660583},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.43567174673080444},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38419461250305176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3670429587364197},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.31433454155921936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17200961709022522}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3567823","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3567823","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:d0cc80d5d1ec42d9abc21879cc6bddd2","is_oa":true,"landing_page_url":"https://doaj.org/article/d0cc80d5d1ec42d9abc21879cc6bddd2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 82247-82260 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3567823","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3567823","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":45,"referenced_works":["https://openalex.org/W90049316","https://openalex.org/W137929096","https://openalex.org/W1857789879","https://openalex.org/W1985352638","https://openalex.org/W2017332073","https://openalex.org/W2053586412","https://openalex.org/W2063959825","https://openalex.org/W2082832591","https://openalex.org/W2088424609","https://openalex.org/W2155529731","https://openalex.org/W2184680703","https://openalex.org/W2215853505","https://openalex.org/W2239694478","https://openalex.org/W2310612427","https://openalex.org/W2401712499","https://openalex.org/W2462052758","https://openalex.org/W2593949166","https://openalex.org/W2760879516","https://openalex.org/W2768883843","https://openalex.org/W2809890364","https://openalex.org/W2906725881","https://openalex.org/W2925788520","https://openalex.org/W3006746595","https://openalex.org/W3042585420","https://openalex.org/W3119107356","https://openalex.org/W3129548626","https://openalex.org/W3177008941","https://openalex.org/W3192803761","https://openalex.org/W3193603477","https://openalex.org/W3198709351","https://openalex.org/W4285343146","https://openalex.org/W4293094723","https://openalex.org/W4295066183","https://openalex.org/W4295067541","https://openalex.org/W4313166648","https://openalex.org/W4313211244","https://openalex.org/W4383567174","https://openalex.org/W4387022596","https://openalex.org/W4387045288","https://openalex.org/W4390971706","https://openalex.org/W4392672416","https://openalex.org/W4403122892","https://openalex.org/W4406753750","https://openalex.org/W4407736284","https://openalex.org/W6802809227"],"related_works":["https://openalex.org/W2163647484","https://openalex.org/W47248985","https://openalex.org/W2000270779","https://openalex.org/W2129486222","https://openalex.org/W3144175025","https://openalex.org/W2042716007","https://openalex.org/W1778024729","https://openalex.org/W1980841486","https://openalex.org/W2043816158","https://openalex.org/W2083844986"],"abstract_inverted_index":{"The":[0,162],"growth":[1],"of":[2,9,19,35,45,121],"international":[3],"trade":[4],"has":[5],"accelerated":[6],"the":[7,14,17,23,43,97,118,122,145,156,167],"development":[8],"waterway":[10],"transportation,":[11],"thereby":[12],"increasing":[13],"demand":[15],"for":[16,79],"construction":[18],"container":[20],"terminals.":[21],"Optimizing":[22],"Berth":[24],"Allocation":[25],"and":[26,72,154,173],"Crane":[27],"Assignment":[28],"Problem":[29],"(BACAP)":[30],"is":[31],"a":[32,58,90,107,112,131,136],"critical":[33],"aspect":[34],"this":[36,39],"process.":[37],"In":[38,144],"paper,":[40],"we":[41,88,129,148],"investigate":[42],"capability":[44,120],"differential":[46],"evolution":[47],"(DE)":[48],"algorithms":[49],"in":[50,75,175],"solving":[51,176],"BACAP":[52,80],"by":[53],"modeling":[54],"berth":[55,132,141],"allocation":[56],"as":[57,106,135],"continuous":[59],"optimization":[60],"problem.":[61],"We":[62],"first":[63],"analyze":[64],"an":[65],"efficient":[66],"clustering":[67],"algorithm,":[68],"Nearest-Better":[69],"Clustering":[70],"(NBC),":[71],"its":[73],"effectiveness":[74],"partitioning":[76],"candidate":[77],"solutions":[78],"into":[81],"multiple":[82],"sub-populations.":[83,123],"Subsequently,":[84],"within":[85],"each":[86],"sub-population,":[87],"propose":[89],"novel":[91],"memetic":[92],"algorithm":[93],"(MA)":[94],"that":[95,166],"utilizes":[96],"Adaptive":[98],"Differential":[99],"Evolution":[100],"with":[101,111,158],"Optional":[102],"External":[103],"Archive":[104],"(JADE)":[105],"global":[108],"optimizer,":[109],"combined":[110],"Neighborhood":[113],"Search":[114],"(NS)":[115],"to":[116,125,139],"enhance":[117],"convergence":[119],"Finally,":[124],"improve":[126],"search":[127],"efficiency,":[128],"introduce":[130],"offset":[133],"distance":[134],"penalty":[137],"mechanism":[138],"minimize":[140],"space":[142],"wastage.":[143],"experimental":[146,163],"section,":[147],"conduct":[149],"experiments":[150],"on":[151],"15":[152],"cases":[153],"compare":[155],"results":[157,164],"four":[159],"existing":[160],"algorithms.":[161],"demonstrate":[165],"proposed":[168],"MA-NBC":[169],"exhibits":[170],"superior":[171],"competitiveness":[172],"performance":[174],"BACAP.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}