{"id":"https://openalex.org/W2808665828","doi":"https://doi.org/10.1109/icaci.2018.8377519","title":"A hybrid encoded memetic algorithm for set covering problem","display_name":"A hybrid encoded memetic algorithm for set covering problem","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2808665828","doi":"https://doi.org/10.1109/icaci.2018.8377519","mag":"2808665828"},"language":"en","primary_location":{"id":"doi:10.1109/icaci.2018.8377519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2018.8377519","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)","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/A5100684651","display_name":"Fang Xu","orcid":"https://orcid.org/0000-0003-1458-9875"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Xu","raw_affiliation_strings":["USTC-Birmingham Joint Research Institution in Intelligent Computation and Its Applications(UBRI), University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USTC-Birmingham Joint Research Institution in Intelligent Computation and Its Applications(UBRI), University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454986","display_name":"Jinlong Li","orcid":"https://orcid.org/0000-0002-9698-1004"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinlong Li","raw_affiliation_strings":["USTC-Birmingham Joint Research Institution in Intelligent Computation and Its Applications(UBRI), University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USTC-Birmingham Joint Research Institution in Intelligent Computation and Its Applications(UBRI), University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"552","last_page":"557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9983000159263611,"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/T12401","display_name":"Scheduling and Timetabling Solutions","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/memetic-algorithm","display_name":"Memetic algorithm","score":0.8339279890060425},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.7996976971626282},{"id":"https://openalex.org/keywords/memetics","display_name":"Memetics","score":0.688108503818512},{"id":"https://openalex.org/keywords/local-search","display_name":"Local search (optimization)","score":0.6434270739555359},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6433717012405396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5715855956077576},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.5561375617980957},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5054404735565186},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.49086815118789673},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.47466185688972473},{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.4634056091308594},{"id":"https://openalex.org/keywords/hybrid-algorithm","display_name":"Hybrid algorithm (constraint satisfaction)","score":0.4417263865470886},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.42710593342781067},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40067654848098755},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40044182538986206},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3174862265586853},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1736532747745514},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.1262311041355133},{"id":"https://openalex.org/keywords/constraint-satisfaction","display_name":"Constraint satisfaction","score":0.10208997130393982}],"concepts":[{"id":"https://openalex.org/C35129592","wikidata":"https://www.wikidata.org/wiki/Q324793","display_name":"Memetic algorithm","level":3,"score":0.8339279890060425},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.7996976971626282},{"id":"https://openalex.org/C51620047","wikidata":"https://www.wikidata.org/wiki/Q23399","display_name":"Memetics","level":2,"score":0.688108503818512},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.6434270739555359},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6433717012405396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5715855956077576},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5561375617980957},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5054404735565186},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.49086815118789673},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.47466185688972473},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.4634056091308594},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.4417263865470886},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.42710593342781067},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40067654848098755},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40044182538986206},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3174862265586853},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1736532747745514},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.1262311041355133},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.10208997130393982},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C176783269","wikidata":"https://www.wikidata.org/wiki/Q5164378","display_name":"Constraint logic programming","level":4,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaci.2018.8377519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2018.8377519","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W84440676","https://openalex.org/W1503619557","https://openalex.org/W1525605957","https://openalex.org/W1534075338","https://openalex.org/W1560337332","https://openalex.org/W1750082253","https://openalex.org/W1917814591","https://openalex.org/W1964214534","https://openalex.org/W1968074599","https://openalex.org/W1973727721","https://openalex.org/W2016207616","https://openalex.org/W2016929496","https://openalex.org/W2028274662","https://openalex.org/W2039862033","https://openalex.org/W2049967755","https://openalex.org/W2053336008","https://openalex.org/W2076570464","https://openalex.org/W2110368321","https://openalex.org/W2115347769","https://openalex.org/W2156557985","https://openalex.org/W2157054705","https://openalex.org/W2162675932","https://openalex.org/W2170186790","https://openalex.org/W2471877100","https://openalex.org/W2582566316","https://openalex.org/W3103464856","https://openalex.org/W4252732074","https://openalex.org/W6631722374"],"related_works":["https://openalex.org/W2318617794","https://openalex.org/W2388961298","https://openalex.org/W2123894366","https://openalex.org/W2122102648","https://openalex.org/W2278624910","https://openalex.org/W2020131881","https://openalex.org/W2024203849","https://openalex.org/W1990478250","https://openalex.org/W2152512538","https://openalex.org/W3034910425"],"abstract_inverted_index":{"Set":[0],"covering":[1],"problem":[2,8],"(SCP)":[3],"is":[4,25,88,103,114],"a":[5,16,33,54,67,96,111],"classical":[6],"NP-hard":[7],"with":[9,21,75,84,99,145],"many":[10],"practical":[11],"applications.":[12],"To":[13],"solve":[14],"SCP,":[15],"hybrid":[17,34,136],"encoded":[18,137],"memetic":[19,138],"algorithm":[20,139],"three":[22],"main":[23],"techniques":[24],"proposed":[26,115,135],"in":[27,48,143],"this":[28],"paper.":[29],"Firstly,":[30],"we":[31,65],"introduce":[32],"encoding":[35],"approach":[36],"to":[37,91,105,116],"define":[38],"two":[39],"genetic":[40],"segments":[41],"f":[42],"or":[43],"e":[44],"ach":[45],"individual":[46],"chromosome,":[47],"which":[49],"the":[50,57,61,72,76,81,85,107,125,134],"first":[51],"segment":[52,59],"encodes":[53,60],"solution,":[55],"and":[56],"second":[58],"learning":[62,118],"information.":[63],"Then,":[64],"provided":[66],"mutation":[68],"operator":[69,113],"guided":[70],"by":[71],"scores":[73],"associated":[74],"gene":[77,82],"bits.":[78],"In":[79,94],"particular,":[80],"bit":[83],"higher":[86],"score":[87],"more":[89],"likely":[90],"be":[92],"mutated.":[93],"addition,":[95],"local":[97],"search":[98],"row":[100],"weighting":[101],"procedure":[102],"used":[104],"improve":[106],"solution":[108],"quality.":[109],"Finally,":[110],"fragment-crossover":[112],"share":[117],"information":[119],"between":[120],"individuals.":[121],"Experimental":[122],"results":[123],"on":[124],"benchmark":[126],"instances":[127],"from":[128],"Beasley's":[129],"OR":[130],"Library":[131],"show":[132],"that":[133],"produces":[140],"competitive":[141],"solutions":[142],"comparison":[144],"other":[146],"meta-heuristics.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}