{"id":"https://openalex.org/W3083175990","doi":"https://doi.org/10.1109/cec48606.2020.9185806","title":"A Training Difficulty Schedule for Effective Search of Meta-Heuristic Design","display_name":"A Training Difficulty Schedule for Effective Search of Meta-Heuristic Design","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3083175990","doi":"https://doi.org/10.1109/cec48606.2020.9185806","mag":"3083175990"},"language":"en","primary_location":{"id":"doi:10.1109/cec48606.2020.9185806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec48606.2020.9185806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Congress on Evolutionary Computation (CEC)","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/A5074763680","display_name":"Jair Pereira","orcid":"https://orcid.org/0000-0002-8412-8081"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jair Pereira Junior","raw_affiliation_strings":["Department of Computer Science, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047785995","display_name":"Claus Aranha","orcid":"https://orcid.org/0000-0003-1390-7536"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Claus Aranha","raw_affiliation_strings":["Department of Computer Science, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080813451","display_name":"Tetsuya Sakurai","orcid":"https://orcid.org/0000-0003-2046-8973"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Sakurai","raw_affiliation_strings":["Department of Computer Science, University of Tsukuba, Tsukuba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","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/T11975","display_name":"Evolutionary Algorithms and Applications","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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9997000098228455,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9955000281333923,"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/computer-science","display_name":"Computer science","score":0.7725380659103394},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.591312825679779},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.5537464022636414},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5375726819038391},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4890354573726654},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4855077266693115},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.445038378238678},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4406850337982178},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3605092763900757},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33238130807876587},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1172579824924469}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7725380659103394},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.591312825679779},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5537464022636414},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5375726819038391},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4890354573726654},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4855077266693115},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.445038378238678},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4406850337982178},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3605092763900757},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33238130807876587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1172579824924469},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec48606.2020.9185806","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec48606.2020.9185806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6399999856948853,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1814515812","https://openalex.org/W1976744965","https://openalex.org/W1977683584","https://openalex.org/W1996387510","https://openalex.org/W2012816980","https://openalex.org/W2025508963","https://openalex.org/W2097571405","https://openalex.org/W2141119792","https://openalex.org/W2152195021","https://openalex.org/W2604662548","https://openalex.org/W2727199084","https://openalex.org/W2793647498","https://openalex.org/W2890854347","https://openalex.org/W2898873842","https://openalex.org/W2960193099","https://openalex.org/W2961419896","https://openalex.org/W2979092933","https://openalex.org/W3209581048","https://openalex.org/W6768967737","https://openalex.org/W6802997697"],"related_works":["https://openalex.org/W2280422768","https://openalex.org/W3143197806","https://openalex.org/W4252555497","https://openalex.org/W3121175838","https://openalex.org/W3016293053","https://openalex.org/W1690653314","https://openalex.org/W2401723157","https://openalex.org/W2065055572","https://openalex.org/W2784269775","https://openalex.org/W2952904874"],"abstract_inverted_index":{"In":[0,117],"the":[1,6,13,63,66,74,101,106,114,131,150,158,163,166,170,184,187,224,232,245,248,259,263],"context":[2],"of":[3,8,65,103,149,165,186,258],"optimization":[4],"problems,":[5],"performance":[7,164],"an":[9],"algorithm":[10,23,83,93],"depends":[11],"on":[12,30,229],"problem.":[14,33,55],"It":[15],"is":[16,212],"difficult":[17,89],"to":[18,46,157],"know":[19],"a":[20,31,40,53,110,207,213],"priori":[21],"what":[22,25],"(and":[24],"parameters)":[26],"will":[27],"perform":[28],"best":[29],"new":[32],"For":[34],"this":[35,118],"reason,":[36],"we":[37,57,120],"previously":[38],"proposed":[39],"framework":[41],"that":[42,61,72,90,181,192,206,220,241],"uses":[43],"grammatical":[44],"evolution":[45],"automatically":[47],"generate":[48],"swarm":[49],"intelligence":[50],"algorithms":[51,168,191,228],"given":[52,264],"training":[54,75,127,155,188,199],"However,":[56,252],"observed":[58],"two":[59],"issues":[60,123],"affected":[62],"results":[64,204,239],"framework.":[67],"The":[68,97,203],"first":[69],"issue":[70,99],"was":[71,100],"sometimes":[73],"problems":[76,132],"are":[77,174],"too":[78,88],"easy,":[79],"and":[80,135,161,177],"any":[81],"candidate":[82,92],"could":[84,94,193,255],"solve":[85,95,194,256],"it":[86,254],"or":[87],"no":[91],"them.":[96],"second":[98],"presence":[102],"parameters":[104,145,222,243],"in":[105,113,129,201,210,223,227],"grammar,":[107],"which":[108,130,173],"causes":[109],"significant":[111],"increase":[112,209],"search":[115],"space.":[116],"work,":[119],"addressed":[121],"those":[122],"by":[124],"investigating":[125],"three":[126],"schedules":[128,156],"start":[133],"easy":[134],"get":[136],"harder":[137],"over":[138],"time.":[139],"We":[140,152,179,217],"also":[141,218],"investigated":[142],"whether":[143],"numerical":[144],"should":[146],"be":[147],"part":[148],"grammar.":[151],"compared":[153,162],"these":[154],"previous":[159],"one":[160],"generated":[167],"against":[169],"traditional":[171,233],"algorithms,":[172],"DE,":[175],"PSO,":[176],"CS.":[178],"found":[180,219],"gradually":[182],"increasing":[183],"difficulty":[185,211],"problem":[189],"produced":[190],"more":[195],"testing":[196,260,265],"instances":[197,261],"than":[198],"only":[200],"10-D.":[202],"suggest":[205],"step-by-step":[208],"better":[214],"approach":[215],"overall.":[216],"including":[221],"grammar":[225,246],"resulted":[226],"par":[230],"with":[231],"meta-heuristics.":[234],"Besides,":[235],"as":[236],"expected,":[237],"our":[238],"show":[240],"removing":[242],"from":[244],"exhibit":[247],"worst":[249],"overall":[250],"performance.":[251],"interestingly":[253],"most":[257],"within":[262],"budget.":[266]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
