Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7647
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dc.contributor.authorZhu, Zhong-Yaoen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-29T04:52:32Z-
dc.date.available2023-03-29T04:52:32Z-
dc.date.issued2002-
dc.identifier.citationProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, 2002, vol. 1, pp. 837 - 842, Article number 1007034en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7647-
dc.description.abstractIn this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation. © 2002 IEEE.en_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002en_US
dc.titleAsynchronous self-adjustable island genetic algorithm for multi-objective optimization problemsen_US
dc.typeConference Proceedingsen_US
dc.identifier.doi10.1109/CEC.2002.1007034-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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