A two-stage memory powered Great Deluge algorithm for global optimization

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dc.contributor.author Acan, Adnan
dc.contributor.author Ünveren, Ahmet
dc.date.accessioned 2015-12-01T13:04:15Z
dc.date.available 2015-12-01T13:04:15Z
dc.date.issued 2014
dc.identifier.citation "A two-stage memory powered Great Deluge algorithm for global optimization", Adnan Acan and Ahmet Ünveren, Soft Computing, DOI 10.1007/s00500-014-1423-5, Springer-Verlag Berlin Heidelberg 2014 en_US
dc.identifier.issn Print ISSN: 1432-7643
dc.identifier.issn Online ISSN: 1433-7479
dc.identifier.uri http://hdl.handle.net/11129/1888
dc.identifier.uri http://dx.doi.org/10.1007/s00500-014-1423-5
dc.description Due to copyright restrictions, the access to the publisher version (published version) of this article is only available via subscription. You may click URI (with DOI: 10.1007/s00500-014-1423-5) and have access to the Publisher Version of this article through the publisher web site or online databases, if your Library or institution has subscription to the related journal or publication. en_US
dc.description.abstract A two-stage memory architecture and search operators exploiting the accumulated experience in memory are maintained within the framework of a Great DeLuge algorithm for real-valued global optimization. The level-based acceptance criterion of the Great DeLuge algorithm is applied for each best solution extracted in a particular iteration. The use of memory-based search supported by effective move operators results in a powerful optimization algorithm. The success of the presented approach is illustrated using three sets of well-known benchmark functions including problems of varying sizes and difficulties. Performance of the presented approach is evaluated and in comparison to well-known algorithms and their published results. Except for a few large-scale optimization problems, experimental evaluations demonstrated that the presented approach performs at least as good as its competitors. en_US
dc.language.iso en en_US
dc.publisher Springer Berlin Heidelberg en_US
dc.subject Computational Intelligence en_US
dc.subject Artificial Intelligence (incl. Robotics) en_US
dc.subject Mathematical Logic and Foundations en_US
dc.subject Control, Robotics, Mechatronics en_US
dc.subject Metaheuristics en_US
dc.subject Great Deluge algorithm en_US
dc.subject Memory-based search en_US
dc.subject Global optimization en_US
dc.title A two-stage memory powered Great Deluge algorithm for global optimization en_US
dc.type Article en_US
dc.description.version Publisher Version(Published Version).


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