{"id":"https://openalex.org/W2144643443","doi":"https://doi.org/10.1109/tevc.2009.2016570","title":"Runtime Analysis of an Ant Colony Optimization Algorithm for TSP Instances","display_name":"Runtime Analysis of an Ant Colony Optimization Algorithm for TSP Instances","publication_year":2009,"publication_date":"2009-08-12","ids":{"openalex":"https://openalex.org/W2144643443","doi":"https://doi.org/10.1109/tevc.2009.2016570","mag":"2144643443"},"language":"en","primary_location":{"id":"doi:10.1109/tevc.2009.2016570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2009.2016570","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"},"type":"article","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/A5056123187","display_name":"Yuren Zhou","orcid":"https://orcid.org/0000-0002-0497-0835"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuren Zhou","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","School of Computer Science & Engineering, South China University of Technology, Guangzhou, China#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science & Engineering, South China University of Technology, Guangzhou, China#TAB#","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5056123187"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":10.9044,"has_fulltext":false,"cited_by_count":113,"citation_normalized_percentile":{"value":0.98482199,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"13","issue":"5","first_page":"1083","last_page":"1092"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9987000226974487,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/travelling-salesman-problem","display_name":"Travelling salesman problem","score":0.8277328610420227},{"id":"https://openalex.org/keywords/ant-colony-optimization-algorithms","display_name":"Ant colony optimization algorithms","score":0.807990550994873},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6297650337219238},{"id":"https://openalex.org/keywords/extremal-optimization","display_name":"Extremal optimization","score":0.6152923703193665},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5647627115249634},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.54731285572052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5232864022254944},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5082959532737732},{"id":"https://openalex.org/keywords/combinatorial-optimization","display_name":"Combinatorial optimization","score":0.4813466966152191},{"id":"https://openalex.org/keywords/metaheuristic","display_name":"Metaheuristic","score":0.43058034777641296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32790514826774597},{"id":"https://openalex.org/keywords/meta-optimization","display_name":"Meta-optimization","score":0.17172986268997192}],"concepts":[{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.8277328610420227},{"id":"https://openalex.org/C40128228","wikidata":"https://www.wikidata.org/wiki/Q460851","display_name":"Ant colony optimization algorithms","level":2,"score":0.807990550994873},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6297650337219238},{"id":"https://openalex.org/C188919014","wikidata":"https://www.wikidata.org/wiki/Q5422296","display_name":"Extremal optimization","level":4,"score":0.6152923703193665},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5647627115249634},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.54731285572052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5232864022254944},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5082959532737732},{"id":"https://openalex.org/C52692508","wikidata":"https://www.wikidata.org/wiki/Q1333872","display_name":"Combinatorial optimization","level":2,"score":0.4813466966152191},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.43058034777641296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32790514826774597},{"id":"https://openalex.org/C4935549","wikidata":"https://www.wikidata.org/wiki/Q6822261","display_name":"Meta-optimization","level":3,"score":0.17172986268997192},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tevc.2009.2016570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2009.2016570","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W85156741","https://openalex.org/W1482913321","https://openalex.org/W1510977876","https://openalex.org/W1543480758","https://openalex.org/W1573676079","https://openalex.org/W1581232621","https://openalex.org/W1683332710","https://openalex.org/W1801849579","https://openalex.org/W1966355747","https://openalex.org/W1993561093","https://openalex.org/W1996375957","https://openalex.org/W2011904305","https://openalex.org/W2015649422","https://openalex.org/W2017708378","https://openalex.org/W2017938154","https://openalex.org/W2039865013","https://openalex.org/W2042096932","https://openalex.org/W2042986967","https://openalex.org/W2052176278","https://openalex.org/W2057398816","https://openalex.org/W2078297643","https://openalex.org/W2093094460","https://openalex.org/W2105039734","https://openalex.org/W2107941094","https://openalex.org/W2118573797","https://openalex.org/W2121489408","https://openalex.org/W2129464780","https://openalex.org/W2130411910","https://openalex.org/W2160241726","https://openalex.org/W2162189348","https://openalex.org/W2165220807","https://openalex.org/W2309459014","https://openalex.org/W2324108981","https://openalex.org/W2397790788","https://openalex.org/W2533104109","https://openalex.org/W2614370452","https://openalex.org/W2984712846","https://openalex.org/W4292083457","https://openalex.org/W4294358747","https://openalex.org/W6635076958","https://openalex.org/W6653428413"],"related_works":["https://openalex.org/W1611875833","https://openalex.org/W2208777194","https://openalex.org/W46882622","https://openalex.org/W1997193297","https://openalex.org/W2146364482","https://openalex.org/W1604040598","https://openalex.org/W2530777107","https://openalex.org/W2406404685","https://openalex.org/W4245157707","https://openalex.org/W1975009952"],"abstract_inverted_index":{"Ant":[0],"colony":[1],"optimization":[2,13],"(ACO)":[3],"is":[4,35,121,127],"a":[5,72],"relatively":[6,49],"new":[7],"random":[8],"heuristic":[9],"approach":[10],"for":[11,91],"solving":[12],"problems.":[14],"The":[15,87,107],"main":[16],"application":[17],"of":[18,26,56,71,100,109,116],"the":[19,24,30,36,42,53,57,60,67,85,110,113,134],"ACO":[20,43,58,74],"algorithm":[21,44,75],"lies":[22],"in":[23],"field":[25],"combinatorial":[27],"optimization,":[28],"and":[29,102,124],"traveling":[31],"salesman":[32],"problem":[33,39],"(TSP)":[34],"first":[37,68],"benchmark":[38],"to":[40,129],"which":[41],"has":[45],"been":[46],"applied.":[47],"However,":[48],"few":[50],"results":[51],"on":[52,59,84,96,133],"runtime":[54,89],"analysis":[55,70],"TSP":[61,98],"are":[62,105],"available.":[63],"This":[64],"paper":[65],"presents":[66],"rigorous":[69],"simple":[73],"called":[76],"(1":[77,92],"+":[78,93],"1)":[79,94],"MMAA":[80,95],"(Max-Min":[81],"ant":[82],"algorithm)":[83],"TSP.":[86],"expected":[88,135],"bounds":[90],"two":[97],"instances":[99],"complete":[101],"non-complete":[103],"graphs":[104],"obtained.":[106],"influence":[108],"parameters":[111],"controlling":[112],"relative":[114],"importance":[115],"pheromone":[117],"trail":[118],"versus":[119],"visibility":[120],"also":[122],"analyzed,":[123],"their":[125],"choice":[126],"shown":[128],"have":[130],"an":[131],"impact":[132],"runtime.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
