{"id":"https://openalex.org/W4399813745","doi":"https://doi.org/10.1007/s10489-024-05603-x","title":"A lightweight CNN-transformer model for learning traveling salesman problems","display_name":"A lightweight CNN-transformer model for learning traveling salesman problems","publication_year":2024,"publication_date":"2024-06-19","ids":{"openalex":"https://openalex.org/W4399813745","doi":"https://doi.org/10.1007/s10489-024-05603-x"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-024-05603-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05603-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05603-x.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05603-x.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039152876","display_name":"Minseop Jung","orcid":null},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minseop Jung","raw_affiliation_strings":["Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101854182","display_name":"Jaeseung Lee","orcid":"https://orcid.org/0000-0002-0204-4547"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeseung Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea","institution_ids":["https://openalex.org/I146429904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016110079","display_name":"Jibum Kim","orcid":"https://orcid.org/0000-0002-7172-5039"},"institutions":[{"id":"https://openalex.org/I146429904","display_name":"Incheon National University","ror":"https://ror.org/02xf7p935","country_code":"KR","type":"education","lineage":["https://openalex.org/I146429904"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jibum Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-7172-5039","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Incheon National University, Incheon, 22012, South Korea","institution_ids":["https://openalex.org/I146429904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016110079"],"corresponding_institution_ids":["https://openalex.org/I146429904"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":3.9905,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.94880942,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"54","issue":"17-18","first_page":"7982","last_page":"7993"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.8505051136016846},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.772533655166626},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7276115417480469},{"id":"https://openalex.org/keywords/travelling-salesman-problem","display_name":"Travelling salesman problem","score":0.6547569632530212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47196733951568604},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4254019558429718},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.29904043674468994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8505051136016846},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.772533655166626},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7276115417480469},{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.6547569632530212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47196733951568604},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4254019558429718},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29904043674468994},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-024-05603-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05603-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05603-x.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10489-024-05603-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-024-05603-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-024-05603-x.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G116806678","display_name":null,"funder_award_id":"IITP-2024-RS-2023-00260175","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G6720347342","display_name":null,"funder_award_id":"NRF-2022R1A4A5034121","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399813745.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1625390266","https://openalex.org/W2055569927","https://openalex.org/W2096041053","https://openalex.org/W2106378689","https://openalex.org/W2163428398","https://openalex.org/W2194775991","https://openalex.org/W2805798351","https://openalex.org/W2861856156","https://openalex.org/W2883780447","https://openalex.org/W2915716523","https://openalex.org/W2963125010","https://openalex.org/W2963163009","https://openalex.org/W2964110616","https://openalex.org/W2998057994","https://openalex.org/W3006028635","https://openalex.org/W3006419636","https://openalex.org/W3146106549","https://openalex.org/W3177318507","https://openalex.org/W3203460037","https://openalex.org/W4210271172","https://openalex.org/W4321113880","https://openalex.org/W4382203174","https://openalex.org/W4388983748","https://openalex.org/W6600109629","https://openalex.org/W6600341180","https://openalex.org/W6601553626","https://openalex.org/W6603884005","https://openalex.org/W6604344240","https://openalex.org/W6702248584","https://openalex.org/W6815235507"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Abstract":[0],"Several":[1],"studies":[2],"have":[3],"attempted":[4],"to":[5,71],"solve":[6],"traveling":[7],"salesman":[8],"problems":[9],"(TSPs)":[10],"using":[11,79,99],"various":[12,144],"deep":[13],"learning":[14],"techniques.":[15],"Among":[16],"them,":[17],"Transformer-based":[18,88,141],"models":[19,37,98,142],"show":[20,106],"state-of-the-art":[21,139],"performance":[22,121,131],"even":[23],"for":[24,64],"large-scale":[25],"Traveling":[26],"Salesman":[27],"Problems":[28],"(TSPs).":[29],"However,":[30],"they":[31],"are":[32,116],"based":[33,55],"on":[34,56],"fully-connected":[35,96],"attention":[36,97],"and":[38,44,61,113,122,135],"suffer":[39],"from":[40,76],"large":[41],"computational":[42,123],"complexity":[43],"GPU":[45],"memory":[46],"usage.":[47],"Our":[48,66,146],"work":[49],"is":[50,69,148],"the":[51,86,100,108,129],"first":[52],"CNN-Transformer":[53,67],"model":[54,68,127],"a":[57,80],"CNN":[58,81,110],"embedding":[59,82,111],"layer":[60,83,112],"partial":[62,102,114],"self-attention":[63,115],"TSP.":[65],"able":[70],"better":[72],"learn":[73],"spatial":[74],"features":[75],"input":[77],"data":[78],"compared":[84],"with":[85],"standard":[87],"models.":[89],"It":[90],"also":[91],"removes":[92],"considerable":[93],"redundancy":[94],"in":[95,119,132,143],"proposed":[101,109,126],"self-attention.":[103],"Experimental":[104],"results":[105],"that":[107],"very":[117],"effective":[118],"improving":[120],"complexity.":[124],"The":[125],"exhibits":[128],"best":[130],"real-world":[133],"datasets":[134],"outperforms":[136],"other":[137],"existing":[138],"(SOTA)":[140],"aspects.":[145],"code":[147],"publicly":[149],"available":[150],"at":[151],"https://github.com/cm8908/CNN_Transformer3":[152],".":[153]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}