{"id":"https://openalex.org/W2151350786","doi":"https://doi.org/10.4304/jcp.8.8.2034-2041","title":"Practical Search Index as a Hardness Measure for Genetic Algorithms","display_name":"Practical Search Index as a Hardness Measure for Genetic Algorithms","publication_year":2013,"publication_date":"2013-07-17","ids":{"openalex":"https://openalex.org/W2151350786","doi":"https://doi.org/10.4304/jcp.8.8.2034-2041","mag":"2151350786"},"language":"en","primary_location":{"id":"doi:10.4304/jcp.8.8.2034-2041","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.8.8.2034-2041","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","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/A5100357950","display_name":"Zhenhua Li","orcid":"https://orcid.org/0000-0002-6212-6384"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenhua Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034853476","display_name":"Erik D. Goodman","orcid":"https://orcid.org/0000-0002-2419-0692"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erik D. Goodman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12329814,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"8","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9975000023841858,"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":0.9805999994277954,"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/measure","display_name":"Measure (data warehouse)","score":0.8014549016952515},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.7044292688369751},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6040604710578918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5435431599617004},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4178647994995117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3230271339416504},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.1921384632587433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12967392802238464}],"concepts":[{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.8014549016952515},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.7044292688369751},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6040604710578918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5435431599617004},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4178647994995117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3230271339416504},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1921384632587433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12967392802238464},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4304/jcp.8.8.2034-2041","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.8.8.2034-2041","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.369.3219","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.369.3219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ojs.academypublisher.com/index.php/jcp/article/viewFile/jcp080820342041/7362/","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W59813247","https://openalex.org/W204927580","https://openalex.org/W1497256448","https://openalex.org/W1533419692","https://openalex.org/W1592766040","https://openalex.org/W1596568617","https://openalex.org/W1597878669","https://openalex.org/W1606791384","https://openalex.org/W1639032689","https://openalex.org/W1933385826","https://openalex.org/W1998835045","https://openalex.org/W2015158691","https://openalex.org/W2047439897","https://openalex.org/W2047600545","https://openalex.org/W2061023988","https://openalex.org/W2066670127","https://openalex.org/W2096571749","https://openalex.org/W2097571405","https://openalex.org/W2107951961","https://openalex.org/W2144946595","https://openalex.org/W2169587965"],"related_works":["https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W4245490552","https://openalex.org/W4225152035","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W1587224694","https://openalex.org/W2911598644","https://openalex.org/W2042127053"],"abstract_inverted_index":{"Use":[0],"of":[1,35,53,76,86,90,95,106,126,143,165],"the":[2,26,36,74,77,82,96,104,107,135,156,159],"Building":[3,37],"Block":[4,38],"Hypothesis":[5],"to":[6,48,73,121],"illuminate":[7],"GA":[8,40,54,145],"search":[9],"behavior,":[10],"as":[11],"pursued":[12],"by":[13,30,81],"J.":[14],"H.":[15],"Holland":[16],"and":[17,42,88,124,129,138,163],"D.":[18],"E.":[19],"Goldberg,":[20],"invites":[21],"additional":[22],"investigation.This":[23],"paper":[24],"investigates":[25],"space":[27,78],"actually":[28],"searched":[29,80],"a":[31],"GA,":[32,83],"in":[33,45,84],"light":[34],"Hypothesis,":[39],"sampling":[41,123,137],"population":[43,115,153,161],"size,":[44,162],"an":[46],"effort":[47],"develop":[49],"more":[50],"quantitative":[51],"measures":[52],"hardness":[55,100],"for":[56],"problems":[57],"where":[58],"building":[59,91,109,127],"block":[60],"sizes":[61,87,105],"can":[62],"be":[63],"estimated.":[64],"A":[65,141],"Practical":[66],"Search":[67],"Index":[68],"(PSI)":[69],"is":[70,117],"defined,":[71],"related":[72],"size":[75,116],"actively":[79],"terms":[85],"numbers":[89],"blocks.":[92],"The":[93],"results":[94],"analysis":[97],"suggest":[98],"that":[99],"depends":[101,132],"strongly":[102],"on":[103,133,147],"largest":[108],"blocks,":[110,128],"premature":[111],"convergence":[112],"prevails":[113],"when":[114],"not":[118],"big":[119],"enough":[120],"allow":[122],"assembly":[125],"appropriate":[130],"sizing":[131],"balancing":[134],"BB":[136],"mixing":[139],"costs.":[140],"set":[142],"simple":[144],"experiments":[146],"classical":[148],"test":[149],"functions":[150],"at":[151],"various":[152],"sizes,":[154],"illustrates":[155],"relationship":[157],"between":[158],"PSI,":[160],"efficiency":[164],"search.":[166]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}