{"id":"https://openalex.org/W101831698","doi":null,"title":"Cellular Genetic Algorithm for Multi-Objective Optimization","display_name":"Cellular Genetic Algorithm for Multi-Objective Optimization","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W101831698","mag":"101831698"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.554.7143","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.554.7143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.res.kutc.kansai-u.ac.jp/~murata/AFSS00-CMOGA.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5084942408","display_name":"Tadahiko Murata","orcid":"https://orcid.org/0000-0002-1654-3945","observed_orcids":["https://orcid.org/0000-0002-1654-3945"]},"institutions":[{"id":"https://openalex.org/I100248960","display_name":"Ashikaga University","ror":"https://ror.org/0330rc745","country_code":"JP","type":"education","lineage":["https://openalex.org/I100248960"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tadahiko Murata","raw_affiliation_strings":["Ashikaga Inst. of Technol"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ashikaga Inst. of Technol","institution_ids":["https://openalex.org/I100248960"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mitsuo Gen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I100248960","display_name":"Ashikaga University","ror":"https://ror.org/0330rc745","country_code":"JP","type":"education","lineage":["https://openalex.org/I100248960"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mitsuo Gen","raw_affiliation_strings":["Ashikaga Inst. of Technol"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ashikaga Inst. of Technol","institution_ids":["https://openalex.org/I100248960"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I100248960"],"apc_list":null,"apc_paid":null,"fwci":0.8681,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.69747102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.5644999742507935,"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"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.5644999742507935,"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"}},{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.2687999904155731,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.11680000275373459,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cellular-genetic-algorithm","display_name":"cellular genetic algorithm","score":0.9829999804496765},{"id":"https://openalex.org/keywords/multi-objective-genetic-algorithm","display_name":"multi-objective genetic algorithm","score":0.8970000147819519},{"id":"https://openalex.org/keywords/pareto-optimal-solutions","display_name":"Pareto optimal solutions","score":0.949999988079071},{"id":"https://openalex.org/keywords/spatially-structured-populations","display_name":"spatially structured populations","score":0.7289999723434448},{"id":"https://openalex.org/keywords/flow-shop-scheduling","display_name":"flow shop scheduling","score":0.7860000133514404},{"id":"https://openalex.org/keywords/bi-objective-optimization","display_name":"bi-objective optimization","score":0.7680000066757202}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.7315763235092163},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5497671365737915},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5302697420120239},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.529723584651947},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.4887373447418213},{"id":"https://openalex.org/C2778106978","wikidata":"https://www.wikidata.org/wiki/Q441898","display_name":"Cellular manufacturing","level":2,"score":0.46221038699150085},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.4621354639530182},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44996848702430725},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4489808976650238},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.44795456528663635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42803192138671875},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4130333960056305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19606053829193115},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.554.7143","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.554.7143","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.res.kutc.kansai-u.ac.jp/~murata/AFSS00-CMOGA.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1496825701","https://openalex.org/W1506821072","https://openalex.org/W1528330097","https://openalex.org/W1532399581","https://openalex.org/W1540072641","https://openalex.org/W1639032689","https://openalex.org/W1905847227","https://openalex.org/W1963828570","https://openalex.org/W2018291578","https://openalex.org/W2024085737","https://openalex.org/W2025490132","https://openalex.org/W2030904951","https://openalex.org/W2044730412","https://openalex.org/W2084996678","https://openalex.org/W2106334424","https://openalex.org/W2118246375","https://openalex.org/W2121365620","https://openalex.org/W2140066605"],"related_works":["https://openalex.org/W127967677","https://openalex.org/W7095280396","https://openalex.org/W7098836393","https://openalex.org/W2360663848","https://openalex.org/W1500096139","https://openalex.org/W4249302577","https://openalex.org/W7097603692","https://openalex.org/W2265933695","https://openalex.org/W116627003","https://openalex.org/W1974593543"],"abstract_inverted_index":{"In":[0,48],"this":[1],"paper,":[2],"we":[3],"show":[4],"how":[5],"cellular":[6,46,50,127],"structures":[7],"can":[8],"be":[9],"combined":[10],"with":[11],"a":[12,36,45,59,62,73,78,85,103,107],"multi-objective":[13,27],"genetic":[14],"algorithm":[15],"(MOGA)":[16],"for":[17,43,101],"improving":[18],"its":[19,119],"search":[20,38,75,79,120],"ability":[21],"to":[22,40,82],"find":[23],"Pareto-optimal":[24],"solutions":[25],"of":[26,35,61,94,99,114,124],"optimization":[28],"problems.":[29,138],"We":[30],"propose":[31],"an":[32],"assignment":[33],"method":[34],"different":[37,74],"direction":[39,80],"each":[41,55,70],"cell":[42,60,71,108,116],"implementing":[44],"MOGA.":[47],"our":[49],"MOGA,":[51],"every":[52],"individual":[53,105],"in":[54,58,84,106],"population":[56],"exists":[57],"spatially":[63],"structured":[64],"space":[65],"(e.g.,":[66],"two-dimensional":[67],"grid-world)":[68],"where":[69],"has":[72],"direction.":[76,121],"Such":[77],"corresponds":[81],"weights":[83],"scalar":[86],"fitness":[87],"function":[88],"defined":[89],"by":[90,131],"the":[91,112,125],"weighted":[92],"sum":[93],"multiple":[95],"objectives.":[96],"The":[97,122],"selection":[98],"parents":[100],"generating":[102],"new":[104],"is":[109,129],"performed":[110],"within":[111],"neighborhood":[113],"that":[115],"based":[117],"on":[118,134],"effectiveness":[123],"proposed":[126],"MOGA":[128],"shown":[130],"computer":[132],"simulations":[133],"two-objective":[135],"flowshop":[136],"scheduling":[137],"1":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-27T00:00:00"}