Global migration strategy with moving colony for hierarchical distributed evolutionary algorithms
In the established hierarchical distributed evolutionary algorithms (HDEAs), object of global migration is individual. To obtain better solutions of concrete problems, global migration strategy with moving colony is proposed in this paper. In global migration based on the proposed strategy, migratio...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2014-11, Vol.18 (11), p.2161-2176 |
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| creator | Li, Chengjun Hu, Guangdao |
| description | In the established hierarchical distributed evolutionary algorithms (HDEAs), object of global migration is individual. To obtain better solutions of concrete problems, global migration strategy with moving colony is proposed in this paper. In global migration based on the proposed strategy, migration object is subpopulation which moves between groups. Such global migration can increase the efficiency of thereafter local migration. Moreover, realizing it even needs no communication because it can be executed by regrouping subpopulations. In our experiments, the basement of parallelism is an EA for the Traveling Salesman Problem. Outcomes of HDEAs based on proposed scheme which have different global migration topology are compared with those of traditional ones on nine benchmark instances. The results show that a HDEA based on the proposed strategy having the ring global topology performs better than traditional HDEAs for high difficulty instances. However, the advantage of that having the random global topology is not so significant because of conflicting migrations arisen from this topology. |
| doi_str_mv | 10.1007/s00500-013-1191-7 |
| format | Article |
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To obtain better solutions of concrete problems, global migration strategy with moving colony is proposed in this paper. In global migration based on the proposed strategy, migration object is subpopulation which moves between groups. Such global migration can increase the efficiency of thereafter local migration. Moreover, realizing it even needs no communication because it can be executed by regrouping subpopulations. In our experiments, the basement of parallelism is an EA for the Traveling Salesman Problem. Outcomes of HDEAs based on proposed scheme which have different global migration topology are compared with those of traditional ones on nine benchmark instances. The results show that a HDEA based on the proposed strategy having the ring global topology performs better than traditional HDEAs for high difficulty instances. However, the advantage of that having the random global topology is not so significant because of conflicting migrations arisen from this topology.</description><identifier>ISSN: 1432-7643</identifier><identifier>EISSN: 1433-7479</identifier><identifier>DOI: 10.1007/s00500-013-1191-7</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Artificial Intelligence ; Cloning ; Computational Intelligence ; Control ; Engineering ; Evolutionary algorithms ; Genetic algorithms ; Mathematical Logic and Foundations ; Mechatronics ; Methodologies and Application ; Migration ; Rings (mathematics) ; Robotics ; Topology ; Traveling salesman problem</subject><ispartof>Soft computing (Berlin, Germany), 2014-11, Vol.18 (11), p.2161-2176</ispartof><rights>Springer-Verlag Berlin Heidelberg 2013</rights><rights>Springer-Verlag Berlin Heidelberg 2013.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-adc74523a220f79ed1a462377cefac349c100db34735248b7591032eefded7f73</citedby><cites>FETCH-LOGICAL-c386t-adc74523a220f79ed1a462377cefac349c100db34735248b7591032eefded7f73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00500-013-1191-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2917902133?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,41488,42557,43805,51319,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Li, Chengjun</creatorcontrib><creatorcontrib>Hu, Guangdao</creatorcontrib><title>Global migration strategy with moving colony for hierarchical distributed evolutionary algorithms</title><title>Soft computing (Berlin, Germany)</title><addtitle>Soft Comput</addtitle><description>In the established hierarchical distributed evolutionary algorithms (HDEAs), object of global migration is individual. To obtain better solutions of concrete problems, global migration strategy with moving colony is proposed in this paper. In global migration based on the proposed strategy, migration object is subpopulation which moves between groups. Such global migration can increase the efficiency of thereafter local migration. Moreover, realizing it even needs no communication because it can be executed by regrouping subpopulations. In our experiments, the basement of parallelism is an EA for the Traveling Salesman Problem. Outcomes of HDEAs based on proposed scheme which have different global migration topology are compared with those of traditional ones on nine benchmark instances. The results show that a HDEA based on the proposed strategy having the ring global topology performs better than traditional HDEAs for high difficulty instances. However, the advantage of that having the random global topology is not so significant because of conflicting migrations arisen from this topology.</description><subject>Artificial Intelligence</subject><subject>Cloning</subject><subject>Computational Intelligence</subject><subject>Control</subject><subject>Engineering</subject><subject>Evolutionary algorithms</subject><subject>Genetic algorithms</subject><subject>Mathematical Logic and Foundations</subject><subject>Mechatronics</subject><subject>Methodologies and Application</subject><subject>Migration</subject><subject>Rings (mathematics)</subject><subject>Robotics</subject><subject>Topology</subject><subject>Traveling salesman problem</subject><issn>1432-7643</issn><issn>1433-7479</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kDFPwzAQhS0EEqXwA9gsMRtsn1M3I6qgIFVigdlyHCd1lcTFTory73EIEhPT3fDed_ceQreM3jNK5UOkNKOUUAaEsZwReYYWTAAQKWR-_rNzIlcCLtFVjAdKOZMZLJDeNr7QDW5dHXTvfIdjnxZbj_jL9Xvc-pPramx847sRVz7gvbNBB7N3JtlKl-SuGHpbYnvyzTAhdBixbmofEqCN1-ii0k20N79ziT6en943L2T3tn3dPO6IgfWqJ7o0UmQcNOe0krktmRYrDlIaW2kDIjcpZ1mAkJBxsS5kljMK3NqqtKWsJCzR3cw9Bv852Nirgx9Cl04qnjOZp8QAScVmlQk-xmArdQyuTR8rRtXUpJqbVKlJNTWpJjKfPTFpu9qGP_L_pm-yangY</recordid><startdate>20141101</startdate><enddate>20141101</enddate><creator>Li, Chengjun</creator><creator>Hu, Guangdao</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>20141101</creationdate><title>Global migration strategy with moving colony for hierarchical distributed evolutionary algorithms</title><author>Li, Chengjun ; Hu, Guangdao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-adc74523a220f79ed1a462377cefac349c100db34735248b7591032eefded7f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Artificial Intelligence</topic><topic>Cloning</topic><topic>Computational Intelligence</topic><topic>Control</topic><topic>Engineering</topic><topic>Evolutionary algorithms</topic><topic>Genetic algorithms</topic><topic>Mathematical Logic and Foundations</topic><topic>Mechatronics</topic><topic>Methodologies and Application</topic><topic>Migration</topic><topic>Rings (mathematics)</topic><topic>Robotics</topic><topic>Topology</topic><topic>Traveling salesman problem</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Chengjun</creatorcontrib><creatorcontrib>Hu, Guangdao</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Soft computing (Berlin, Germany)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Chengjun</au><au>Hu, Guangdao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Global migration strategy with moving colony for hierarchical distributed evolutionary algorithms</atitle><jtitle>Soft computing (Berlin, Germany)</jtitle><stitle>Soft Comput</stitle><date>2014-11-01</date><risdate>2014</risdate><volume>18</volume><issue>11</issue><spage>2161</spage><epage>2176</epage><pages>2161-2176</pages><issn>1432-7643</issn><eissn>1433-7479</eissn><abstract>In the established hierarchical distributed evolutionary algorithms (HDEAs), object of global migration is individual. To obtain better solutions of concrete problems, global migration strategy with moving colony is proposed in this paper. In global migration based on the proposed strategy, migration object is subpopulation which moves between groups. Such global migration can increase the efficiency of thereafter local migration. Moreover, realizing it even needs no communication because it can be executed by regrouping subpopulations. In our experiments, the basement of parallelism is an EA for the Traveling Salesman Problem. Outcomes of HDEAs based on proposed scheme which have different global migration topology are compared with those of traditional ones on nine benchmark instances. The results show that a HDEA based on the proposed strategy having the ring global topology performs better than traditional HDEAs for high difficulty instances. However, the advantage of that having the random global topology is not so significant because of conflicting migrations arisen from this topology.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00500-013-1191-7</doi><tpages>16</tpages></addata></record> |
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| subjects | Artificial Intelligence Cloning Computational Intelligence Control Engineering Evolutionary algorithms Genetic algorithms Mathematical Logic and Foundations Mechatronics Methodologies and Application Migration Rings (mathematics) Robotics Topology Traveling salesman problem |
| title | Global migration strategy with moving colony for hierarchical distributed evolutionary algorithms |
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